On-Farm Evaluation of Maize and Legume Intercropping for Improved Crop Productivity in the Mid Hills of Nepal

On-farm evaluation of maize and legume intercropping for improved crop productivity in the mid hills of Nepal

Name student(s): Arun Thapa

Period: 6th Period

Farming Systems Ecology Group Droevendaalsesteeg 1 – 6708 PB Wageningen - The Netherlands ______

On-farm evaluation of maize and legume intercropping for improved crop productivity in the mid hills of Nepal

Name student(s): Arun Thapa Registration number student: 810312827090 Credits: 36 ECTs Code number/name course: FSE- 80436 Period: 6th Period Supervisor(s): Maria Victoria Alomia Hinojosa, Jeroen Groot Examiner: dr.ing. Johannes Scholberg

PREFACE

This thesis is submitted in partial fulfilment of the requirement for a Master degree in Plant Science. It contains work done from June 2014 to February 2015. The writing of the report has gone through ups and downs. Especially in the beginning I experienced trouble defining the research topic. This was finally succeeded with the support of my supervisors of Farming System Ecology group. This thesis is primarily aimed at farmers in mid hills of Nepal where large proportion of population rely on maize based farming system. I hope it will be of interest to the scientific and academic communities as it tries to look for compatibility of research on intercropping on farmers’ fields. This report summarises 8 months joyful hardship job with a hope to synthesise good results with recommendations. First of all, I would like to thank The Netherlands organization for international cooperation in higher education (Nuffic) for the Netherland Fellowship Programmes that they offered me to pursue my M.Sc. studies. I also extend my gratitude to Wageningen University for granting me a permission to participate in the course of Plant Science with specialization on Crop Science. I am deeply indebted to my supervisor dr.ir. Jeroen Groot of the Farming System Ecology group, whose interest in my work has been a constant source of inspiration. My gratitude are extended to Maria Victoria Alomia Hinojosa, Ph.D. candidate of Farming System Ecology group, for her comments and suggestions from the planning stage of experiment to accomplishment of the field experiment. In the finishing stages, Dr Groot and ir. Victoria’s attentions are gratefully acknowledged. I also thank Mr Resham K.C. and Mr. Krishna Gupta, Field supervisors of CIMMYT- CISA (Nepal) and Mr. Sudip Shahi, intern on CIMMYT-CISA (Nepal) who helped me during my field work with untiring interest. The Regional Agriculture Research Centre (RARS), Khajura, Nepal is indeed acknowledged for allowing me to make use of their laboratory. Finally I sincerely want to thank my family and friends for their moral support and patience.

Arun Thapa

ABSTRACT

An on-farm experiment on maize and legume intercropping was conducted on local farmers’ fields in Dadeldhura district, far western region of Nepal under rain fed conditions during the rainy season from June to November, 2014. The objective of this study was to evaluate the effect of maize-legume intercropping systems for improved crop productivity in maize-based farming systems in the mid hills of Nepal. Treatments followed in this experiment were maize sole (Mz), soybean sole (Sb), cowpea sole (Cp), maize-soybean (MzSb) with 1:1 row arrangement and maize-cowpea (MzCp) with 1:1 row arrangement. Maize grain yield and morphological plant parameters (plant height, leaf length, leaf width, active leaf number, girth, grain number per cob) of maize were not affected by any of the cropping systems showing strong competitive ability of maize in intercropping. Soybean plant parameters (plant height, number of nodes, number of branch, branch weight, number of leaves, leaves weight, number of pods per plant) were adversely affected by the presence of maize plants, whereas for cowpea there was no difference in plant parameters (pod length and number of pods per plant) between sole cowpea and the intercropping system. Grain yield of soybean and fresh pod yield of cowpea were significantly reduced by 58% and 46% respectively in intercropping compared to sole cultivation. Higher light interception was observed in intercrops, maize-soybean (MzSb) and maize-cowpea (MzCp), at 60 and 67 days after sowing (DAS) compared to sole cropping. At 50 DAS lower weed density was observed in intercropping systems than in sole maize and sole soybean. Land Equivalent Ratio was greater than one in intercropping systems, 1.54 and 1.69 for maize-soybean (MzSb) and maize- cowpea (MzCp), respectively. The same trend was observed for Area Time Equivalent Ratio for maize-soybean (MzSb) and maize-cowpea (MzCp) with value of 1.39 and 1.61, respectively. The economic evaluation on the other hand indicated that net benefit was higher for maize-cowpea (MzCp) intercropping but from marginal analysis higher return benefit (832 %) was obtained in maize-soybean (MzSb).

Key words : maize, legumes, intercropping, cropping systems, sole cropping

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LIST OF ABBREVIATION

AGDP Agriculture Gross Domestic Product ATER Area Time Equivalent Ratio CBS Central Bureau of Statistics CIMMYT International Maize and Wheat Improvement Centre DAP Di-Ammonium Phosphate DAS Days After Sowing DM Dry Matter EC Emulsifiable Concentrate FP Farmer Practice FWE Fresh Weight Ear FWG Fresh Weight Grain FYM Farm Yard Manure GFB Gross Field Benefit Ha Hectare HH House Hold HI Harvest Index LAI Leaf Area Index LER Land Equivalent Ratio LSD Least Significant Difference LU Livestock Unit MC Moisture Content MOP Muriate of Potash MRR Marginal Rate of Return NB Net Benefit NRs Nepalese Rupees NLSS Nepal Living Standard Survey OM Organic Matter PAR Photosynthetically Active Radiation TVC Total Variable Cost VDC Village Development Committee

LIST OF TABLES

Table 1. Soil properties of different farms on two experimental sites...... 13 Table 2. Participating farmers at on-farm trial on two experimental sites...... 14 Table 3. Effect of cropping system on leaf length and leaf width of maize on different Days after sowing (DAS)...... 25 Table 4. Effect of cropping system on maize yield characteristics ...... 25 Table 5. Effect of cropping system on soybean vegetative growth and yield parameters...... 26 Table 6. Effect of cropping system on cowpea yield parameters...... 26 Table 7. Effect cropping system on yield ...... 30 Table 8. Effect of cropping system on partial Land Equivalent Ratio, Total Land Equivalent Ratio (LER) and Area Time Equivalent Ratio (ATER) ...... 32 Table 9. Effect of cropping system on maize-legume stover Dry Matter (DM) yield...... 32 Table 10. Effect of cropping system on Harvest Index of maize, soybean and cowpea ...... 34 Table 11. Net benefit analysis of different cropping system...... 34 Table 12. Marginal rate of return analysis of different cropping system ...... 35 Table 13. Socioeconomic categorization of participating farmers in study...... 36 Table 14. Farmers’ perspectives on practices applied in the field trial...... 41 Table 15. Shift in production factors ...... 50

LIST OF FIGURES

Figure 1. Map indicating Experimental sites in Far western region of Nepal...... 12 Figure 2. Monthly rainfall and mean air temperature during growing season 2014...... 13

Figure 3. Row arrangement of maize ‘Mz’ ( ), soybean ‘Sb’ ( ) and cowpea ‘Cp’ ( ) for different cropping system...... 15 Figure 4. Effect of cropping system on maize plant height on different days after sowing (DAS)...... 24 Figure 5. Effect of cropping system on weed density per 0.25 m2 ...... 27 Figure 6. Effect of cropping system on weed fresh weight...... 28 Figure 7. Photosynthetically Active Radiation (PAR) interception of different cropping system on different days after sowing (DAS)...... 29 Figure 8. Effect of cropping system on Leaf Area Index (LAI)...... 29 Figure 9. Influence of Leaf Area Index (LAI) on light interception...... 30 Figure 10. Effect of cropping system on crop yields at different farm on two different sites . 31 Figure 11. Effect of cropping system on maize and legume stover DM yield at different farm on two different sites...... 33 Figure 12. Net benefit curve of different cropping system...... 36 Figure 13. Adoption of different cropping system by farmers in Kharif (rainy) season (Survey report, Victoria, 2014)...... 37 Figure 14. Maize grain yield of local varieties at different farmers field ...... 38 Figure 15. Yield gap of maize grain yield between different cropping system and farmers practice...... 38 Figure 16. Maize yield (Mg ha-1) among different farmer categories in different cropping system and farmers practices...... 39 Figure 17. Gap in stover DM yield and annual DM feed requirement among farmer categories on different cropping system and farmer practice...... 40 Figure 18. Farmer’s preference on technologies before and after harvesting...... 42

TABLE OF CONTENT

PREFACE ...... ii ABSTRACT ...... iii LIST OF ABBREVIATION ...... iv LIST OF TABLES ...... v LIST OF FIGURES ...... vi 1. INTRODUCTION ...... 1 2. LITERATURE REVIEW ...... 4 2.1. Intercropping as a practice ...... 4 2.2. Basis of intercropping ...... 5 2.2.1. Yield advantage ...... 5 2.2.2. Environmental resource use efficiency ...... 5 2.2.3. Biological N fixation and improved soil fertility ...... 7 2.2.4. Weed suppression and reduction of pests and diseases ...... 7 2.2.5. Improving feeding value of crop residues ...... 7 2.2.6. Stability against total crop failure ...... 7 2.3. Factors affecting successful intercropping ...... 8 2.3.1. Competition for resources ...... 8 2.3.2. Crop arrangement ...... 8 2.3.3. Adapting intercropping to farm ...... 9 2.4. Design for studying yield advantage in intercropping ...... 9 2.5. Assessment of intercropping productivity ...... 9 2.5.1. Land equivalent ratio ...... 9 2.5.2. Area time equivalent ratio ...... 10 2.6. Partial budget analysis ...... 11 3. MATERIALS AND METHODS ...... 12 3.1. Experimental Set-Up ...... 12 3.1.1. Location, soil and climate ...... 12 Source : Soil analysis data (Victoria, 2014) ...... 13 3.1.2. Design and Treatments ...... 13 3.1.3. Plant and varieties used ...... 14 3.1.4. Land preparation and planting ...... 14 3.2. Management practices ...... 16 3.2.1. Fertilizer application ...... 16 3.2.2. Weed management ...... 16 3.2.3. Pest/disease management ...... 16

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3.2.4. Gap filling ...... 16 4. DATA COLLECTION ...... 16 4.1. Maize and Legume Crop Assessment ...... 17 4.1.1. Maize plant characteristic ...... 17 4.1.2. Maize leaf area and leaf area indices ...... 17 4.1.3. Maize grain yield ...... 18 4.1.4. Maize grain per cob ...... 18 4.1.5. Maize stover yield ...... 18 4.1.6. Soybean plant attributes ...... 19 4.1.7. Soybean leaf area and leaf area indices ...... 19 4.1.8. Soybean grain yield ...... 20 4.1.9. Soybean stover yield ...... 20 4.1.10. Cowpea fresh pod yield ...... 20 4.1.11. Cowpea stover yield ...... 21 4.2. Radiation measurement ...... 21 4.3. Weed sampling ...... 21 4.4. Harvest Index ...... 21 4.5. Assessing productivity of intercrop ...... 21 4.6. Economic assessment of sole and intercropping system ...... 22 4.7. Maize yield under farmer practice ...... 22 4.8. Farmer perspective ...... 23 5. DATA ANALYSIS ...... 23 6. RESULTS ...... 24 6.1. Vegetative growth parameters of maize ...... 24 6.2. Legume vegetative growth and yield parameters ...... 25 6.3. Weed population and weed fresh weight ...... 26 6.4. Light interception and Leaf Area Index ...... 28 6.5. Yield advantage ...... 30 6.6. Stover/biomass DM yield of maize and legumes ...... 32 6.7. Economic advantage analysis ...... 34 6.8. Farm characterization and farmer perception ...... 36 7. DISCUSSION ...... 43 7.1. Crop yield and yield determining factors ...... 43 7.2. Yield advantage and economic benefits ...... 44 7.3. Farmers’ perspectives and preferences ...... 45 7.4. Yield variability among farms ...... 46 7.5. Practical implications ...... 48

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8. CONCLUSION ...... 51 9. REFERENCES ...... 52 10. APPENDIX ...... 58 i. Gantt chart for measuring different parameter during on farm trial...... 58 ii. Maize plant height on different cropping system ...... 59 iii. Maize leaf length and girth size of different cropping system ...... 60 iv. Maize leaf width on different cropping system ...... 61 v. Maize active leaf on different cropping system ...... 62 vi. Soybean yield parameter ...... 63 vii. Cowpea yield component ...... 63 viii. Light interception on different cropping system ...... 64 ix. Leaf Area Index of different cropping system ...... 65 x. Weed density and weed fresh weight on different cropping system ...... 66 xi. Maize and legume yield on different cropping system ...... 68 xii. Maize and legume stover DM yield on different cropping system ...... 69 xiii. Partial LER, Total LER , ATER and HI of maize, soybean and cowpea on different cropping system...... 71 xiv. Maize grain yield and stover DM yield on farmers practice ...... 72 xv. Most repeatedly occuring problematic weeds at on experimental sites ...... 73

1. INTRODUCTION

In Nepal, maize is the second staple food crop after rice. It is grown in 80% of total cultivated area in hilly region. Low land and irrigated land in the Terai (plain region) and the lower mid hills are dominated by rice-based farming systems with wheat, maize and cash crops as secondary products. Whereas upland and non-irrigated land (mainly hills) is characterized by maize-based farming systems (Paudel et al., 2011). The mid-hills of Nepal are characterized by complex and labour-intensive farming systems with low returns. Mixed crop-livestock farming is predominant with high degree of subsistence together with close integration between crops, livestock and forest components (Dhungana et al., 2012). About 70% of arable land in the hills can be classed as unirrigated hill slopes (bari land), and only about 30% as irrigated (khet land). Soil fertility under the traditional farming system has been maintained by repeated addition of various amounts of organic compost/manure that comes from livestock, ranging from 3 to 21 Mg/ha/annum (Paudel, 1992). But this seems to be not enough for nutrient balance to get enough productivity. Next to the crop sector, livestock is the second most dominant subsector of the agriculture accounting for 30% of AGDP (FAO, 2005). Almost two thirds of the agriculture households in the country rear cattle as a source of income, draft power and manure (Joshy, 2010). In the mid hills, livestock raising fulfils the nutrient demands by providing milk, meat and eggs but there is negative effects of overstocking and baring of common grazing and forest land resource (Das and Shivakoti, 2006). Fragmentation of land is common practice in Nepal. As the population grows land gets subdivided due to inheritance, sales and other form of transaction. The Nepal Living Standard Survey (2010/11) shows the average size of agriculture land holding in the mountain, hill and terai with 0.7 ha, 0.6 ha and 0.8 ha respectively (CBS, 2011). Low rainfall and high temperature severely reduce the yield of the major cereals in Dadeldhura district (Bhandari, 2013). In fact, the agriculture is far below the potential level as consequence farming has remained subsistence oriented. Food production from subsistence farming is sufficient only for 3-8 months depending upon the location, type and size of the land and seasonal factors (Karki and Gurung, 2012). Thus migrating within Nepal and abroad are regular trends to relieve the food scarce periods (Maharjan et al., 2013b). Most of the adult men migrate within Nepal or abroad especially to India leaving 25% of households headed by women (CBS, 2011). Consequently there is feminization in agriculture with a bulk of work load and responsibilities due to shortage of male labour (Maharjan et al., 2013a). In addition extra time has to be allocated to collect communal natural resources such as fuel

1 wood, fodder/forage outside the farm. There is also fundamental challenges with the restricted access to communal forest which have significant impact on livestock farming (Dhakal et al., 2005). Sources of available feed for the livestock in the mid hill districts of Nepal are mainly crop residues, fallow grazing land and fodder from the forest (Devendra and Gardiner, 1995). Currently in Nepalese farming systems, available feeds cannot sustain the cattle requirement throughout the year mostly in the critical period being the dry season at October to May (Upreti and Shrestha, 2006) the time when both the quality and the quantity are very poor (Tiwari et al., 2013). The common feeding diets comprise 50% maize stover, these diets are often too low in crude protein amount, limiting the cattle production (Dzowela, 1985). The introduction of legumes with improved management practices like row arrangement in maize based farming system in the mid hills is a promising strategy for increasing crop and livestock productivity. Yield advantages from intercrop as compared to sole cropping are often recognized as complementary effects of component crops depending upon several factors including differences in plant architecture, rooting patterns, competitive advantages and potential nitrogen fixing capacity of the legume (Thobatsi, 2009). Efficient utilization of available resources like sunlight, moisture and soil nutrients results in relative higher yields in intercropping than crops grown as pure stand (Peksen and Gulumser, 2013). Intercropping has advantage over sole cropping on land use efficiency (Belel et al., 2014), economic benefits and soil fertility (Khan et al., 2011) and weed control (Zaviehmavadat et al., 2013). Corn legume mixtures established in narrow strip arrangement increases the forage quality by increasing crude protein yield per hectare and reducing neutral detergent fibre without decreasing yield as compared to that of sole cropped corn (Reta Sánchez et al., 2010). The objective of this research is to evaluate the effect of maize-legume intercropping for improved crop productivity on maize based farming system in the mid hills of Nepal. Specific Objectives 1. To determine the effect of maize legume intercropping on biomass (grain and stover/straw) of maize and legumes. 2. To examine whether there is possible advantage in terms of land use efficiency on intercropping system. 3. To quantify the economic costs and benefits of intercropping maize with selected legume crops.

Hypotheses 1. Maize grain yield is higher when intercropped with a legume than as sole crop. 2. Intercropping maize and legume is much more efficient in utilizing the available resources which results in profitable in terms of land utilization than sole cropping. 3. Intercropping maize with legume crops yield greater economic returns than the pure stand maize.

2. LITERATURE REVIEW

Growing two or more crops at the same time and on the same piece of land is referred to as intercropping and has been practiced as an age old technology, which is still used in most of the developing countries (Machado, 2009). This technology allows improved resource capture due to dissimilar plant growth habits and resource demands. This could lead to increased productivity per unit of area (Fortin and Pierce, 1996). Although intercropping is an ancient practice nowadays there is increased interest in understanding the underlying processes and seeking different ways to increase the productivity of such systems. The key to increase productivity in intercropping is to understand the nature of interaction between crops in the mixtures (Ranganathan, 1993). Some research revealed advantages for intercropping systems over sole cropping such as higher grain yield, greater land use efficiency (Willey, 1990) and improvement of soil fertility through biological nitrogen fixation from legume crop component (Papendick et al., 1976). But also there is competition between crops for different growth stimulating factors like water, light, nutrients and as a result this competition leads to reduction in plant growth performance (Baumann et al., 2001).

2.1. Intercropping as a practice

In general, farmers practice intercropping under indigenous technological condition as a strategy for profit maximization and risk minimization (Norman, 1974). Intercropping is associated with small land holding farmers. This practice allow them to gain extra income from additional crops. It is also related with copping strategy from risk where failure of one crop can be compensated with other in the mixture. There are four types of intercropping that seem most practical (Mousavi and Eskandari, 2011): 1. Mixed intercropping, growing two or more crops together without any distinct row arrangement, 2. Row intercropping, growing two or more crops at the same time where at least one crop is planted in rows, 3. Strip intercropping, growing two or more crops together in wide enough strips which allow for separate crop production and also close enough for the component crops to interact, 4. Relay intercropping, growing component crops in relay so that growth cycles of both component crops overlap.

2.2. Basis of intercropping

In an intercrop system row arrangement alters the amount of light transmission to lower layers of the crops and affects the competition of component crops for growth stimulating resources like light, water and nutrients. There are many reports concerning the positive effects and also superiority of intercrops as compared to pure stands. The most important advantages of intercropping described below.

2.2.1. Yield advantage

Producing more than a single crop on the same piece of land is one of the main reasons for choosing intercropping. This type of cropping system is mainly targeted for resource poor farmers who have limited access to external inputs like nitrogen fertilizers which is the main production limiting factor (Reynolds et al., 1994). Intercropping system is associated with biological fixation of atmospheric nitrogen by legume crops so it is considered as an economic friendly method for higher production with lower external inputs (Mousavi and Eskandari, 2011). The importance of legume in mixed cropping is not only because they provide protein and high yield but also it enabled farmers to cope with soil degradation (Chang, 1977). Intercropping wheat with beans has advantages in land utilization efficiency and economic performance when compared with sole crop (Bulson et al., 1997). Land equivalent Ratio (LER) increased to a maximum of about 1.48 and 1.31 by intercropping maize and sorghum with soybean when compared with cereal sole crops (Mohta and De, 1980). Taking in to consideration of increased yield, performance of intercropping system is better than sole cropping together with balanced food supply for human consumption (Vandermeer, 1992).

2.2.2. Environmental resource use efficiency

Different crops are used in intercropping systems whose requirements for growth factors might be different. So there is advantage in this system in comparison to sole cropping due to complementary in resource utilization and as a result there is an increase in yield from the more effective use of environmental resources (Jensen, 1996).

2.2.2.1. Water use efficiency

The availability of water is the most important factor to determine productivity. For farmers growing crops under rain fed conditions, like in Nepal, is the major production limiting factor. Water use efficiency is higher in maize legume intercropping than in sole cropping if soil

5 water is not limiting but under drought condition water use efficiency in intercrop is lower compared to sole cropping (Ofori and Stern, 1987). In intercropping system with two component crops such as legume and cereals, there may be higher water use efficiency than sole cropping if both components have different rooting pattern so that they can explore a larger total soil volume (Willey, 1990).

2.2.2.2. Nutrient use efficiency

Intercropping system allows for spatial and temporal increase in nutrient uptake. There is efficient use of available nutrient and higher nitrogen uptake in intercropping system than sole cropping if the component crops in the system have different rooting pattern (Dalal, 1974). Temporal advantage in nutrients uptake occur when crops in an intercropping system have their peak nutrients demands at different times (Anders et al., 1994).

2.2.2.3. Radiation use efficiency

Solar radiation is the radiant energy for photosynthesis, which ultimately sets the potential for crop productivity. Biomass accumulation is proportional to the Photosynthetically active radiation (PAR) that plant intercept throughout its growing period. (Alados et al., 1996). The advantage of intercropping over alternative cropping system is that it either increases the interception of solar radiation or has greater radiation use efficiency which leads to improved productivity per unit of incident radiation (Keating and Carberry, 1993). The intercropping advantage has been largely attributed to differences in the time of maturity of the component crops. So time differences in harvesting between crops leads to effective use of limiting resources, especially light (Martin and Snaydon, 1982). Shading and reduced assimilates production will have the least effect on yield if the competition occurs in vegetative stage growth but greatest effect on reproductive stage (Keating and Carberry, 1993). Leaf area Index (LAI) is the amount of green leaf area per unit of ground area. The fraction of the incoming PAR which is absorbed by canopies of component crops in intercrop systems mainly depends on the LAI and canopy structure (Zhang et al., 2008). Taller cereals shades the legume and at high densities cause reduced growth and yield of companion legume. At low maize density, bean received 50% of the incident light where as 20% at high maize density. This high density results in lower yield of intercrop comprising only 30% of sole crop yield (Ofori and Stern, 1987) .

2.2.3. Biological N fixation and improved soil fertility

Sustainable agriculture relies greatly on renewable resources like biological nitrogen fixation, which plays an important role in maintaining soil fertility. Legumes play an important role in natural ecosystem with their ability to fix atmospheric nitrogen in symbiosis (Graham and Vance, 2003). Biological nitrogen fixation is dependent upon physical, environmental, nutritional and biological factors which means that inclusion of any nitrogen fixing plant system does not guarantee increased contribution to the soil nitrogen pool (Wani et al., 1995) and none of these factors should be considered in isolation as all are interconnected in the control of nitrogen fixation (Van Kessel and Hartley, 2000).

2.2.4. Weed suppression and reduction of pests and diseases

Intercrop systems use resources more efficiently and are able to remove more resources as compared to mono crops system thus decreasing the amount of resources available for weed growth (Carruthers et al., 1998). High crop densities in intercrops resulted in faster increase of LAI and so that the weeds are outcompeted for resources (Bilalis et al., 2010). Another advantage of intercropping is its ability to reduce pest and disease damage. Generally reduction in insect pests damage in intercropping can be divided in to three main hypotheses, first: companion crops break down the ability of pest attack to main crop, second: companion crop may act as a trap to prevent damage of the main crop from pest and disease, third is creating habitat for natural enemies (Mousavi and Eskandari, 2011).

2.2.5. Improving feeding value of crop residues

Intercropping systems are considered as an option for low resource farmers to feed their animals better as it include forage legume with food crops that improve the nutrient value of crop residues (Devendra, 1997). Maize and cowpea intercropping increases the green fodder yield and crude protein in maize forage (Dahmardeh et al., 2009). Maize and legume intercropping significantly reduce neutral detergent fibre (NDF) and acid detergent fibre (ADF) concentration. Thus increase the digestibility of the forage (Javanmard et al., 2009).

2.2.6. Stability against total crop failure

When two or more crops are grown together on the same piece of land and one of them fails due to disaster may be helpful over time in intercropping system as other less damaged crop in the mixture will compensate the failure (Trenbath, 1999). Such type of yield stability is

7 very important particularly for those farmers who have limited resources and income, especially low input/high risk environments (Willey et al., 1980).

2.3. Factors affecting successful intercropping 2.3.1. Competition for resources

Crops with faster initial growth may be dominant over resource use such as better root access to soil resources. If total plant population in intercrops are higher than in the sole crops, under stress conditions, intercropping yields could be lower than sole crop yields because of increased competition for soil moisture and nutrients (Natarajan and Willey, 1986). The amount of light intercepted by the component crops in the intercrops system depends upon the geometry of the crops and foliage architecture. Taller cereals shades the legume and high plant population density causes reduced growth and yield of companion legume (Chui and Shibles, 1984; Ofori and Stern, 1987). Light intensity influences plant growth and development which leads to affect biomass accumulation and distribution (Ifenkwe et al., 1989).

2.3.2. Crop arrangement

Intercrop productivity depends upon the interaction of the three main factors i.e. genetic constitution of component crops, growth environment (soil and atmosphere, weeds, pests and diseases, etc.) and agronomic management practices. The interaction of these factors should be optimized in such a way that the available limiting resources are utilized most effectively (Fukai and Trenbath, 1993). When two or more crops are growing together there should have an adequate space to allow effective edaphic interaction, such as light penetration in the canopies of both the taller and shorter components (Chui and Shibles, 1984). In many experiments crop population (number of plants per unit area) and space allocation has been achieved by varying the number of rows of each crop at constant within row spacing (Willey and Rao, 1981). Spatial arrangement of single rows of maize alternating with single rows of soybean gave the higher maize grain yield compared to maize planted with double rows of soybean (Addo-Quaye et al., 2011). Distinguishing between temporal and spatial factors can be useful in intercropping because it leads to greater resource capture and greater resource conversion efficiency (Willey, 1990).

2.3.3. Adapting intercropping to farm

Farmers perception is the key factor for the success of technologies and their perception reflect their socioeconomic status (Kamanga et al., 2003). For any technology to be able to accept by farmers, it should have advantage on biological, environment, economic and social factors. Farmers generally avoid taking unnecessary risk, so acceptance of technology is only possible when advantages are clearly visible. In addition such technologies should be evaluated through participation with farmers.

2.4. Design for studying yield advantage in intercropping

There is an intensive competition between the component crops if they have the same growth duration. Small changes in the micro environment of the system can affect the performances of component crops (Fukai and Trenbath, 1993). Two types of design have been used to study competition in binary mixture as stated by Snaydon (1991). One is replacement design, where a given number of plants of one crop (i) is replaced by the same number of plants of another crop (j) and a mixture is formed in such a way that the population of each crop is lower in the mixture as compared to sole stand. Second is additive design, where one crop (j) is added to the another crop (i) present in the sole stand as result the total population is higher in the mixture than in the sole stand. Additive intercrops may still be productive because of complete capture of resources but the least competitive crop may suffer when resources are depleted too rapidly. Additive design give valid and interpretable values of each of the indices of competition regardless of density or population (Snaydon, 1991). On the other hand for biological interpretation one frequently assumes an additive design (Vandermeer, 1992).

2.5. Assessment of intercropping productivity 2.5.1. Land equivalent ratio

The important reason for growing mixed crops simultaneously is to increase productivity and diversify production per unit area as compared to sole cropping. Land Equivalent Ratio (LER) is as an indication of combined yield for evaluating the effectiveness of intercropping which is defined as the total land area required under sole cropping to give the yields obtained in the intercropping system (Ofori and Stern, 1987). It is expressed as:

Land Equivalent Ratio (LER) = (Y ij /Y ii) + (Y ji / Y jj) (1)

Where Y is the yield per unit area, Yii and Yjj are sole crop yields of the component crops i and j, and Y ij and Y ji are intercropped yields. The partial LER values Li and Lj, represent the ratios of the yields of crops i and j when grown as intercrops. Thus,

Partial LER (Li) = (Yij / Yii) (2)

Partial LER (Lj) = (Y ji/ Yjj) (3)

LER is the sum of the two partial land equivalent ratios so that,

LER = Partial LER (Li) + Partial LER (Lj) From the calculation given above, three conditions can be drawn (Ofori and Stern, 1987): when LER= 1, this represents no yield advantage in mixed cropping as same yields of each crop can be obtained with sole cropping at recommended density as with mixture, without changing the total area of land. When LER < 1, the yield obtained in a mixed cropping can be achieved in sole cropping from a smaller area. When LER > 1, there is yield advantage and larger area of land is needed to produce the same yield of each crop with sole crop at recommended density than with mixed cropping. The partial LER gives an indication of the relative competitive abilities of the components of an intercropping system. Thus the species with higher partial LER are considered to be more competitive for growth limiting factors than the species with lower partial LER (Mead and Willey, 1980). LER does not give the production of biomass instead it represents the yield advantage or disadvantage of intercrops compared to sole crops.

2.5.2. Area time equivalent ratio

In contrast to LER, the Area Time Equivalent Ratio (ATER) considers growth duration (life cycle) of individual crop which is more suitable to compare sole and intercrops as the growth period (life cycle) of the main crop and companion crop are different (Hirpa, 2013). The Area Time Equivalent Ratio proposed by Hiebsch and McCollum (1987) as modification of LER takes in to account of time (life cycle) from planting to harvesting. It is calculated as:

ATER = (Liti + Ljtj)/T (4)

Where Li and Lj are partial LERs of component crops i and j, ti and tj are the duration (days) for crops i and j, and T is the duration (days) of the whole intercropping system.

2.6. Partial budget analysis

A partial budget shows the effect of changes in farm operations and is based on a unit. Partial budget analysis is used for comparing the impact of technological change on farm costs and returns. It is like an enterprise budget which includes only variable input cost excluding fixed input cost (Horton, 1982). Basic concept used at Partial budget analysis for on farm research recommended by CIMMYT from agronomic data to farmer recommendation (CIMMYT, 1988) is illustrated below : The first step in partial budget analysis is the calculation of net present value of benefit in which field prices and costs are used to compute.

Net Benefit (NB) = Gross field benefit (GFB) –Total Variable cost (TVC) (5)

Next step is dominance analysis to select potential profitable treatments. Here treatment with net benefit equal to or lower than other treatment with lower total variable input costs is considered to be dominated. Dominated treatment are eliminated for further steps in the marginal analysis. However, for effective recommendation, Marginal Rate of Return (MRR) is calculated to know the cost increment required to obtain increment in net benefit.

MRR (a>>b) (%) = [∆ NB (a>>b)/ ∆ TVC (a>>b)] × 100 (6)

Where ∆ NB (a>>b) and ∆ TVC (a>>b) are the change in net benefit and total variable cost due to change from a to b. Criteria for partial budget analysis (Horton, 1982): • If net benefit remains the same or decreases the new technology should be rejected because it is not more profitable than the farmer’s present technology. • If net benefit increase and total variable costs remain the same or decrease, the new technology should be accepted because it is clearly more profitable than the farmer’s technology. • If both net benefit and total variable costs increase marginal rate of return should be analysed. The higher the marginal rate of return, the more attractive an alternative technology is from an economic point of view.

3. MATERIALS AND METHODS 3.1. Experimental Set-Up 3.1.1. Location, soil and climate

The on-farm field trial was conducted at two sites of the Dadeldhura district (Figure. 1) namely Amargadhi Municipality (Littregaun) and Samaiji VDC (Mahargaun and Koteli) under rain fed conditions over a period of rainy season from June to November, 2014. Geographically Dadeldhura district is situated at 29° 18’ N latitude and 80° 34’ 60 E longitude with an average elevation of 1745 meter above mean sea level. To conduct the trial in both sites altogether 11 farmers were selected with inclusion of heterogeneity of farm size, resource allocation and socio-economic status. The criteria for farm selection was inclusion of wealthy, medium and poor farms based on income source, size of the farm, number of livestock and ethnicity. Before that, an initial survey (Base line survey: Victoria, 1 2014) was done to know the Figure 1. Map indicating Experimental sites in Far western region of Nepal. socioeconomic status of the farmers. Additional information regarding meteorological data (temperature and rainfall) during the growing season is summarized in Figure. 2 and soil type in experimental site of different farms are given in Table 1.

1 The red stars indicates the two experimental sites. 12

300.0 35

250.0 30 25 200.0 20 150.0 15 100.0

Precipitation (mm) (mm) Precipitation 10 50.0 5 Average Temperature ( ° C) ( ° Temperature Average 0.0 0

Months 2014

Precipitation (mm) Average Temperature (° C)

Figure 2. Monthly rainfall and mean air temperature during growing season 2014.

Table 1. Soil properties of different farms on two experimental sites. Soil depth (cm) N% P% g C/kg soil pH 0-10 0.14 0.05 16.9 6.28 Farmer 1 10-30 0.09 0.05 10.1 6.35 0-10 0.13 0.05 14.1 6.19 Farmer 2 10-30 0.13 0.05 13.8 6.18 0-10 0.18 0.06 21.1 6.5 Farmer 5 10-30 0.12 0.05 14.6 6.56 0-10 0.20 0.07 20.1 6.28 Farmer 6 10-30 0.12 0.07 19.6 6.33 0-10 0.21 0.06 27.5 6.23 Farmer 7 10-30 0.15 0.05 14.7 6.49 0-10 0.19 0.04 19.0 6.41 Farmer 9 10-30 0.11 0.03 6.7 6.59 0-10 0.19 0.05 22.5 6.46 Farmer 10 10-30 0.13 0.04 13.3 6.51 Source : Soil analysis data (Victoria, 2014)

3.1.2. Design and Treatments

Randomised complete block design with three crops, namely maize, soybean and cowpea comprising 5 treatments were used. The treatments consists of , Treatment 1 Sole Maize denoted as ‘Mz’ Treatment 2 Sole Soybean denoted as ‘Sb’ Treatment 3 Maize-Soybean with 1:1 row arrangement denoted as ‘MzSb’ Treatment 4 Maize-Cowpea with 1:1 row arrangement denoted as ‘MzCp’ Treatment 5 Sole Cowpea denoted as ‘Cp’

Each farmer was considered as a replication of the treatments comprising farmer as a block. The maize crop was allowed to have full population in addition to accommodate some population of legume crops as farmers want to keep the full population of maize crops because of land scarcity. The list of farmers and field size for the treatment is presented in Table 2.

Table 2. Participating farmers at on-farm trial on two experimental sites. Plot size (m2) S.n. Farmers’ Name Municipality/VDC* Location – Ward no. for each treatment 1 Nikmati BK Amarghadi Municipality Littre gaun - 11 10.8 2 Ganesh Bhd Khadka Amarghadi Municipality Littre gaun - 11 10.8 3 Lal Bhd Khadka Amarghadi Municipality Littre gaun - 11 10.8 4 Rima Khadka Amarghadi Municipality Littre gaun - 11 10.8 5 Bhim Bhd Khadka Amarghadi Municipality Littre gaun - 11 10.8 6 Surbey Tamata Amarghadi Municipality Littre gaun - 11 10.8 7 Sita Khadka Samijee VDC Koteli - 7 10.8 8 Basu Dev Bhatta Samijee VDC Koteli - 7 10.8 9 Dev Bista/ Parbati Bista Samijee VDC Mahar gaun- 8 10.8 10 Bahadur Bista Samijee VDC Mahar gaun- 8 10.8 11 SureshTamata/Indra Tamata Samijee VDC Koteli - 7 9.0 * VDC refers to Village Development Committee

3.1.3. Plant and varieties used

For trial set up mainly three crops were used namely maize, soybean and cowpea. The varieties were ‘Rajkumar’ for maize, ‘Puja’ for soybean and ‘Tane bodi’ for cowpea. Hybrid variety was used for maize and improved varieties for soybean and cowpea.

3.1.4. Land preparation and planting

The land was ploughed just after onset of the rains using mini tiller and minimum tillage. The planting of the maize and legume was done on the same day i.e. June 2nd and 3rd, 2014 at Littregaun and Samaiji VDC respectively. Gross plot area for each treatment was 10.8 m2 except for one farmer only with 9 m2 due to narrow terrace in his field. Sole cowpea treatment was conducted only with two farmers. Maize was planted at the normal spacing of 70 cm between rows and 25 cm between plants within the row. The soybean was planted with 50 cm between rows and 10 cm interplant. For maize and soybean with 1:1 row arrangement intercrop maize was 70 cm with the same interplant spacing as in the sole maize treatment and

14 maize to soybean was 35 cm with the same inter plant spacing as in the sole soybean treatment. For maize and cowpea with 1:1 row arrangement, inter row and inter plant spacing for maize was 70 cm and 25 cm respectively and maize to cowpea spacing was 35 cm with 10 cm cowpea interplant spacing. For sole cowpea treatment inter row and inter plant distance was 70 cm and 10 cm respectively. The detailed plan of crop row arrangement for the intercropping systems of maize, soybean and cowpea is shown in Figure. 3.

Figure 3. Row arrangement of maize ‘Mz’ ( ), soybean ‘Sb’ ( ) and cowpea ‘Cp’ ( ) for different cropping system.

3.2. Management practices

3.2.1. Fertilizer application

Farmers applied FYM along the fields. This practice could not be avoided as some farmers applied it just after the previous crop. Urea was manually applied as topdressing at 25 DAS and 60 DAS for the supplement of nitrogen. At the time of sowing supplement of nitrogen and phosphorous was done from Di-ammonium Phosphate (DAP-18:46:0) and for potassium from Muriate of Potash (MOP-0:0:60) as a basal dose. In legume recommended fertilizer was applied only as basal dose. Application rate for the above mentioned mineral fertilizers that was applied in the experimental field are as follows: Sole maize: 150-60-40 kg ha-1 Sole Soybean: 10-40-30 kg ha-1 Maize: soybean and maize: cowpea intercrops: 60-60-40 kg ha-1

3.2.2. Weed management

Weeding was done manually 2 times on 25 DAS and 50 DAS on both sites following the common practice that farmers do in their field using a small weeding hoe.

3.2.3. Pest/disease management

The cowpea was affected by aphids in both sole and intercropped plot in 6 farms at 25 DAS. In order to control aphids, insecticide was applied on the affected plots with Chlorpyriphos 50% +Cypermethrin 5% EC at a dose of 2 ml per litre of water.

3.2.4. Gap filling

Due to drought conditions during germination the emergence percentage was poor for all three component-crops (maize, soybean and cowpea) so gap filling was done once by re- sowing 15 days after first sowing.

4. DATA COLLECTION Gantt chart for data collection of different crops and other measurements taken during experiment is given on Appendix 10.i.

4.1. Maize and Legume Crop Assessment 4.1.1. Maize plant characteristic

Maize plant height was measured 22 DAS by selecting 6 random plants per plot for sole maize (Mz), maize-soybean (MzSb) and maize-cowpea (MzCp). Plant height was measured from the base of the plant to the tip of the plant. In the meantime leaf length, leaf width and growth stage was also determined for the same treatments. Leaf length and leaf width was measured from fully expanded last two leaves. Growth stage was determined by leaf collar method where leaf blade visually breaks form the sheath and stalks of maize plant. Vegetative growth stages was based on the number of visible leaf collar. Growth stage of maize was determined by labelling numerically as V1, V2 and through V (n), where (n) represents fully expanded leaf i.e. visible leaf collar. These measurements were done until the reproductive stage (R1) of maize in this case 76 DAS. R1 stage was determined by any silk visible outside the husk leaves. Active leaf of maize was counted from 60 DAS at 7 days intervals until 74 DAS and continued from 90 DAS till 104 DAS with same interval days. At the time of harvest (110 DAS) plant height and stem girth was measured from 10 plant samples. Stem girth was measured immediately after plant height measurement at the midpoint of the plant height. For all measurements comprising leaf length, leaf width and plant height were done by using plastic tape measure and self-retracting tape measure.

4.1.2. Maize leaf area and leaf area indices

The formula proposed by Krishnamurthy et al. (1974) was used to determine leaf area and leaf area index (Issahaku, 2010). Measurement was done at R1 stage i.e. 76 DAS.

Leaf area = k × (l × w) (7)

Where, l = leaf length; w = leaf width; k = factor (in cereals = 0.75). Leaf area index was calculated by dividing the total area of leaves by total land area it occupied.

Leaf area index (LAI) = [k × (l × w)]/A (8)

Where A = total land area occupied by leaves Average leaf length and leaf width was obtained from each plant in order to get average leaf area of single leaf. Further to calculate leaf area of each plant average leaf area of single leaf was then multiplied by number of the functional leaves present in each plant. Total land

17 area occupied by leaves was determined by taking 6 maize plant in to consideration which occupies 1.05 m2. Considering 6 plants was based upon the previously randomly selected for measuring maize plant characteristics mentioned in section 4.1.1. Finally Leaf Area Index (LAI) was calculated with ratio of total leaf area of 6 plants by the area of ground covered by 6 plants.

4.1.3. Maize grain yield

Maize grain was harvested at physiologically mature stage i.e. 110 DAS from a net harvest area of 5.6 m2 for 10 farmers and 4.2 m2 for 1 farmer having small plot. Net harvest area was determined by removing 1 border row from each side of experimental plot and 2 border plants from each end of remaining rows. Entire ear sample from net harvested area was weighed to get fresh weight of ears. 10 representative ears were taken and fresh weight was determined. After shelling 10 ear samples, fresh weight of grain was determined and grain moisture content was measured with grain moisture meter. Shelling percentage was calculated by dividing fresh weight grain by fresh weight ear of sample ears respectively. Finally grain yield per plot was calculated adjusted to 15% moisture content and then grain yield was calculated in Mg per hectare.

Shelling percentage (%) = FWG10/FWE10 (9)

Grain yield per plot adjusted to 15 % moisture content:

FWEH × Shelling percentage × (100 – MC)/85 (10)

Where, FWG10 is Fresh weight Grain of 10 sample ears, FWE10 is Fresh Weight Ear of 10 sample ears, MC is moisture content in the grain at the time of harvest measured with grain moisture meter, FWEH is weight of fresh ear harvested from net harvest area.

4.1.4. Maize grain per cob

At the time of harvest 10 cobs were randomly selected from net harvest plot. The number of grains was counted for each cob and later number from 10 cobs was averaged to get the number of grains per cob.

4.1.5. Maize stover yield

Randomly 5 maize plants were selected to measure maize stover yield at the time of harvesting, 110 DAS. Fresh weight of 5 plants was determined and stalks of selected plants

18 were cut in to small pieces. Separate subsamples of leaves and stems were taken, weighing 500 gram each, to dry the stover samples at 70 ̊ C for 24 hours. After removing samples from the drying oven it was immediately weighed in digital weighing machine to determine the final oven dry weight of the subsample. Dry weight of 5 plants was determined by multiplying fresh weight of 5 plants to the ratio of dry weight of subsample to fresh weight of subsample. Further stover dry weight per plot was estimated based on the plant population from net harvest area. Finally then stover yield in Mg per hectare was calculated.

4.1.6. Soybean plant attributes

Plant height, number of nodes, branch number and leaves per plant were measured by destructive methods at 76 DAS by selecting randomly 3 plants from each plot of sole soybean (Sb) and maize-soybean (MzSb). Plant height was measured with a self-retracting tape measure from tip of the shoot to base of the stem. Branch weight and leaves fresh weight were measured with portable digital balance in the field. Number of pods per plant was determined 130 DAS at the time of harvest from 10 sample plants from each plot for both treatments.

4.1.7. Soybean leaf area and leaf area indices

A destructive method was used to calculate leaf area of soybean. Leaf area measurement was done by a simple, inexpensive and accurate method using photographs and the ImageJ program (O'neal et al., 2002). 76 DAS 3 plants samples were taken from each plot for treatments sole soybean (Sb) and maize-soybean (MzSb), from which all leaves were separated and leaves of each plant were placed on a white paper board. The dimension of white paper board was fixed to 140 cm × 100 cm. A photograph was taken using a digital camera to analysed in ImageJ program for the calculation of leaf area. First Image was changed to 8 bit type and threshold to make binary. Further scale was set in order to obtain number of pixel per known distance (pixel/cm in this case) for particle analysis. The summary obtained from particle analysis indicate the area covered by the leaves in the area of the white paper board. Finally, leaf area for each plant was estimated from the percentage of the white paper board covered by leaves. For sole soybean (Sb) 1m2 area was considered as ground area. Total leaf area covered by soybean in 1m2 was determined by multiplying the number of plant per square meter with leaf area of each plant. For intercropped soybean, the same process was applied as sole soybean (Sb) except for ground cover was 1.05m2. This was taken from area covered by 6 maize plants

19 in order to calculate Leaf Area Index for intercropping system. Finally Leaf area index was calculated from the ratio of total leaves area to total land area it occupied (Watson, 1958).

4.1.8. Soybean grain yield

The pods from sole soybean (Sb) was harvested at maturity i.e. 130 DAS, from net harvest area of 6.5 m2 for 10 farmers and 5.2 m2 for 1 farmer having small plot. Net harvest plot for sole soybean (Sb) was set same as maize. For intercropped soybean, the whole plot was considered as net harvest plot because of poor growth performance of soybean i.e. 10.8 m2 for 10 farmers and 9 m2 for 1 farmer. The pods were threshed to determine fresh weight of grain. The grain moisture content was measured by a grain moisture meter. Finally grain yield per plot was calculated adjusted to 15% moisture content and then grain yield was calculated in Mg per hectare.

4.1.9. Soybean stover yield

Ten soybean plants were selected randomly at the time of harvesting, 130 DAS, to estimate soybean stover yield from same net harvest area as for soybean grain yield. Fresh weight of 10 sample plants was determined and stalks of selected plant were cut in to small pieces. Subsamples of 500 gram were taken to dry the stover samples at 70 ̊ C for 24 hours. After removing samples from the drying oven they were immediately weighed to determine the final oven dry weight. Dry weight of 10 sample plants were determined by multiplying fresh weight of 10 sample plants to the ratio of dry weight of subsample to fresh weight of subsample. Further stover dry weight per plot was estimated based on the plant population from net harvest area. Finally, the stover yield in Mg per hectare was calculated.

4.1.10. Cowpea fresh pod yield

Harvesting of fresh pod started 66 DAS and was carried out 4 times from harvest area of 10.8 m2 from maize-cowpea (MzCp) and sole cowpea (Cp). For sole cowpea (Cp) and intercropped cowpea (MzCp), the whole plot was considered as net harvest plot because plants were intertwined with each other. Fresh weight of harvested pod was weighed at each harvest and cumulative weight was determined after final harvest 90 DAS. Finally, pod yield per plot was calculated and converted in Mg per hectare. At harvest time, 10 pods were randomly selected to determine pod length in both treatments.

4.1.11. Cowpea stover yield

Due to lower plant population in the cowpea plots, compared to the soybean and maize, a smaller number of random plant samples was selected to estimate cowpea stover yield at 90 DAS. Stover yield was determined in the same process as for soybean stover yield mentioned in section 4.1.9.

4.2. Radiation measurement

Photosynthetically active radiation (PAR in µmol m-2 s-1) of all treatments were measured from 60 DAS until 97 DAS at 7 days interval using Quantum sensor (MQ 301) with a sensor length of 70 cm. Two measurements were taken in each treatment between the row at the top of the canopy and below the canopy. The fraction of PAR intercepted was calculated as,

PARi = [1- ( I/ I0)] × 100. (11)

-2 -1 Where PARi (%) is the fraction of total incident PAR intercepted, I0 (in µmol m s ) the total incident radiation above canopy and I (in µmol m-2 s-1) the radiation below canopy.

4.3. Weed sampling

Weed density was sampled twice from 0.5×0.5 m2 quadrant areas in each treatment before weeding at 25 and 50 DAS. Fresh weight of weed biomass per 0.25 m2 was determined for all the treatments at same time with portable digital weighing balance.

4.4. Harvest Index

Harvest index was calculated by using following formula, Harvest Index (HI) (%)=[Grain yield (Mg/hectare)/Total biomass yield (Mg/hectare)]×100 (12)

4.5. Assessing productivity of intercrop

Maize-soybean and maize-cowpea competitive behaviours were determined by Land Equivalent Ratio (LER) and Area time equivalent ratio (ATER) which were calculated by using equation 1, 2, 3 and 4 as described in section 2.5.1 and 2.5.2 respectively.

4.6. Economic assessment of sole and intercropping system

Partial budgeting model recommended by CIMMYT (1988) was applied for economic evaluation to estimate the gross value of the component crops using the adjusted yield at 2014 market price for the yield and inputs. Grain yields adjusted to 15% moisture content in maize and soybean were evaluated at farm gate price but in case of cowpea fresh pod was used. The major variable costs included in analysis were seed, fertilizer, weeding and staking2. Labour cost for fertilizer application, weeding and staking were also included in variable cost on person days per hectare. The existing rates paid to farm labour at the local site were used to estimate the labour cost. Net benefit was calculated using equation 5 as described in section 2.6. The increasing net benefit with increasing costs was then compared across treatments. Dominance analysis was calculated following the criteria that any treatment that has net benefit equal or lower than other treatment with lower cost is dominated. The dominated treatment was eliminated and marginal analysis carried out for the un- dominated treatment applying equation 6 as described in section 2.6. Acceptable minimum rate of return was fixed for the acceptance of the alternative decisions because of cost and risk. Saka et al. (2007) have set the acceptable minimum rate of return between 40-100%. Acceptable minimum rate of return for farmers is the sum of total capital cost and net return to farm management. Most of the farmers in the current study area have limited access to formal loans so they rely on informal loans, like revolving funds, farmer groups savings and credit funds, and personal relatives. The interest rate of these informal loans varies from 3- 10% per month. The growing period (from land preparation to harvest) of both maize and legume in intercrop is 130 days (in case of soybean) in our trial. If we consider the interest rate to be 10% per month then the cost of capital is 40.5% (10% per month × 4.5 months). I assumed that the majority of the farmers in that area considered such intercropping practice to be profitable only when it would give 100% returns to management. So in such condition acceptable minimum rate of return will be 140.5% (100% + 40.5%) and this acceptance is taken as basis for analysing marginal return.

4.7. Maize yield under farmer practice

Maize yield estimation under farmer practice was done from a 4 m2 plot. These plots were managed under farmers practice without any intervention by current study. Later on at harvest

2 Staking refers to the sticks used as support for cowpea 22 time, the same process was applied as mentioned in section 4.1.3 and 4.1.5 to calculate maize grain yield and maize stover DM yield respectively.

4.8. Farmer perspective

Farmers’ field visit and interaction was done at 86 DAS in order to know their perception about intercropping based on biophysical characteristics of crop components. Thirty six farmers including both participating farmers in trial and non-participating (neighbour) farmers were asked to give their view about the reasons for incorporating three major management practices that were applied in trial, i.e. using a mini tiller for soil preparation, legume integration and line sowing. Preference ranking for the different treatments was done through scoring. Farmers were asked to score 1 and 0 for most preference and least preference respectively. Such preference mapping was done twice, first at the mid of crop growth period and second after harvest through an interview. Further data were presented on preference percentage of farmers on technologies. Farm characterization of participating farmers was done on the basis of size of land they own, i.e. marginal farmers owning 0.1-0.3 ha, small farmers owning 0.3-0.5 ha, medium farmers owning 0.5-3 ha, and large farmers with >3 ha of land (Timsina, 2010). From participating farmers the cropping system they practice in their farm during study period was mapped by surveys conducted by Victoria Alomia (2014).

5. DATA ANALYSIS

Statistical analysis was conducted using GenStat, 16th Edition-GenStat. The experiment was analysed as a randomized complete block design experiment. Analysis of Variance was conducted to determine the effect of cropping pattern. Treatments were compared using the least significant difference (LSD) test at the P < 0.05.

6. RESULTS 6.1. Vegetative growth parameters of maize

The on-farm experiments did not present significant differences in maize plant height between cropping system at different days after sowing except for 37 DAS (P=0.009) and 44 DAS (P=0.046) (Figure 4). At 37 DAS plant height was significantly higher in maize-soybean (MzSb) with 61.2 cm followed by maize-cowpea (MzCp) and sole maize (Mz) with 60.1 cm and 56.2 cm respectively. But there was no significant difference in maize-soybean (MzSb) and maize cowpea (MzCp). Plant height was significantly higher in maize-soybean (MzSb) at 44 DAS with 103.1 cm. However, no difference was observed between sole maize (Mz) with 94.2 cm and maize-cowpea (MzCp) with 100.0 cm. Despite no statistical significant in plant height at the time of harvest (110 DAS), higher plant height was observed in sole maize (Mz) followed by maize-soybean (MzSb) and maize-cowpea (MzCp) with 302.2 cm, 300.2 cm and 293.1 cm respectively. Overall maize plant height showed a sigmoid trend throughout the growing season for all cropping system.

350

300

250

200 Mz 150 MzSb Height (cm) (cm) Height 100 MzCp

0 0 10 20 30 40 50 60 70 80 90 100 110 120 Days After Sowing

Figure 4. Effect of cropping system on maize plant height on different days after sowing (DAS). Where Mz is sole maize, MzSb is intercropped maize-soybean; MzCp is intercropped maize-cowpea.

LSD 0.05 = 3.14 and 6.98 for 37 DAS and 44 DAS respectively.

There was no effect of cropping system at different days after sowing on leaf length and leaf width of maize plant except at 76 DAS (P=0.015) leaf length was significantly larger in maize-soybean (MzSb) but no difference was observed between sole maize (Mz) and maize- cowpea (MzCp) (Table 3). There was no effect of cropping system on active leaf number at

different days after sowing, same is the result with no significant difference on girth size and number of grains per cob at different cropping system (Table 4).

Table 3. Effect of cropping system on leaf length and leaf width of maize on different Days after sowing (DAS). Treatments 22 DAS 30 DAS 37 DAS 44 DAS 51 DAS 62 DAS 76 DAS

Mz 17.4 36.3 55.4 73.7 92.9 92.7 46.7 a * Leaf length MzSb 19.8 39.1 58.6 76.8 94.9 91.1 50.8 b MzCp 19.1 38.1 58.6 77.2 94.8 90.7 46.5 a * LSD P<0.05 NS NS NS NS NS NS NS 3.14

Mz 1. 9 3.7 6.2 8.4 10.1 10.1 6.0 Leaf width MzSb 2.1 4.0 6.5 8.7 10.3 10.0 6.3 MzCp 2.0 3.8 6.5 8.6 10.1 9.7 5.9 ** LSD P<0.05 NS NS NS NS NS NS NS NS Where Mz is sole maize, MzSb is intercropped maize-soybean, MzCp is intercropped maize-cowpea. Different letters within the characteristics indicate significant mean difference (P<0.05). * For comparison of leaf length between cropping system. ** For comparison of leaf width between cropping system. NS indicate for Non-Significant.

Table 4. Effect of cropping system on maize yield characteristics Active leaf number Girth (cm) Grain per Treatments At harvest 60 DAS 67 DAS 74 DAS 90 DAS 97 DAS 104 DAS cob (no.) (110DAS)

Mz 11.1 14.5 14.5 13.0 11.8 11.4 6.4 608.6 MzSb 11.2 14.6 14.4 12.8 11.6 11.4 6.2 600.4 MzCp 10.7 14.3 14.0 12.5 12.1 11.8 6.1 583.7

LSD P<0.05 NS NS NS NS NS NS NS NS Where Mz is sole maize, MzSb is intercropped maize-soybean, MzCp is intercropped maize-cowpea. NS indicate for Non-Significant and DAS for Days After Sowing.

6.2. Legume vegetative growth and yield parameters

The result of analysis of variance shows that significant differences (P<0.05) were observed between the cropping system on vegetative growth parameter of soybean (Table 5). A significant higher vegetative growth parameter was recorded in sole cropping rather than intercrop cropping system except for plant height which was higher in the intercrop. There was no significant difference in yield parameters of cowpea, however higher values were observed at intercropping rather than sole (Table 6). 25

Table 5. Effect of cropping system on soybean vegetative growth and yield parameters. Plant Branch Leaves No. of No. of No. of No. of Pods Treatments height weight weight node (#) branch (#) leaves (#) per plant (#) (cm) (gram) (gram)

Sb 125.6 a 45.3 b 6.3 b 125.7 b 141.5 b 83.4 b 75.7 b MzSb 154.9 b 20.0 a 2.9 a 49.1 a 64.6 a 41.5 a 53.5 a

LSD P<0.05 23.49 5.53 1.36 20.88 25.11 13.10 16.03 Sb is sole soybean, MzSb is intercropped maize-soybean.

Different characters indicate means differ significantly with LSD P<0.05.

Table 6. Effect of cropping system on cowpea yield parameters. Treatments Fresh Pod length (cm) No. of pods per plant (#)

MzCp 39.8 6. 2 Cp 39.3 5.3

LSD P<0.05 NS NS MzCp is intercropped maize-cowpea and Cp is sole cowpea. NS mean does not differ significantly.

6.3. Weed population and weed fresh weight

Most repeatedly occuring problematic weed species found in the field trial sites during experiment were Commelina bengalensis, Digitaria species, Cyperus rotundus and Ageratum conyzoides (Annex 10xv). The first three belong to monocot while the later one belongs to dicot family. Dicot weeds were increased after first weeding and monocot weeds were lowered except for sole maize. Weed population and weed fresh biomass as affected by different cropping system on two observation date i.e. 25 DAS and 50 DAS is given in Figure 5 and Figure 6. Statistical analysis of the data shows that there was no significant difference in weed fresh biomass for different cropping system on both observation date. However highest weed fresh weight was observed in sole cowpea (Cp) with 24.1 g per 0.25 m2 and lowest in sole soybean (Sb) with 12.8 g per 0.25 m2 at 25 DAS. At 50 DAS sole soybean (Sb) rank highest with 191 g per 0.25 m2 and lowest was in maize-cowpea (MzCp) with 133 g per 0.25 m2. Cropping system did not show any significant difference in weed density at 25 DAS. But at 50 DAS (P<0.001) there was significant difference in weed density between different cropping systems. The highest weed density was observed in sole maize (Mz) and lowest in

26 sole cowpea (Cp). Maize-soybean (MzSb) and maize-cowpea (MzCp) did not show a significant difference in weed density at 50 DAS, however lower than sole maize (Mz) and sole soybean (Sb) (Figure 5). Weed density was decreased by 46% and 55% in maize-soybean (MzSb) and maize-cowpea (MzCp) as compared with sole maize. At 25 DAS, the highest weed density was observed in maize-soybean (MzSb), while the highest weed fresh biomass was observed in sole cowpea (Cp). Where as lowest weed density and weed fresh biomass was obtained in sole maize (Mz) on same observation day. Similarly, 50 DAS the highest weed density was observed in sole maize (Mz) while the highest weed fresh biomass in sole soybean (Sb). On the same observation day, the lowest weed density was recorded on sole cowpea (Cp) while, the lowest weed fresh biomass on maize-cowpea (MzCp) This shows dissimilar trend between weed density and weed fresh biomass.

200 d * 180

160 NS 140 c NS NS NS 120 NS b 100 25 DAS b 80 50 DAS

Weed density (number) (number) density Weed 60 a 40

0 Mz Sb MzSb MzCp Cp

Treatments

Figure 5. Effect of cropping system on weed density per 0.25 m2 where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea. Different letters indicate the means differ significantly (P<5%) with LSD (0.05) = 25.41*. NS indicate for Non-Significant and DAS for Days after Sowing.

250 ) 2 200 NS

NS NS NS 150 NS 25 DAS

100 50 DAS

50 Weed fresh weight (gram per 0.25 m per (gram fresh weight Weed NS NS NS NS NS

0 Mz Sb MzSb MzCp Cp

Treatments

Figure 6. Effect of cropping system on weed fresh weight. Where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea. NS indicate Non-Significant and DAS for Days after Sowing.

6.4. Light interception and Leaf Area Index

The percentage of PAR interception was significantly (P<0.05) affected by cropping system at different days after sowing except for 60 DAS (Figure 7). In the intercrop treatments namely, maize-soybean (MzSb) and maize-cowpea (MzCp) the mean of PAR interception was significantly higher (P<0.05) than for sole maize (Mz). But there was no difference between intercropped treatment, sole soybean (Sb) and sole cowpea (Cp) except for 90 and 97 DAS where light interception was higher for treatments with soybean (Sb and MzSb).

100 95 90 Mz 85 Sb 80 MzSb 75 MzCp PAR interception (%) interception PAR 70 50 55 60 65 70 75 80 85 90 95 100 Cp Days After Sowing

Figure 7. Photosynthetically Active Radiation (PAR) interception of different cropping system on different days after sowing (DAS). Where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea. Significant at LSD (0.05 ) = 4.76, 1.55, 3.49, 3.44 for 67 DAS, 74 DAS, 90 DAS and 97 DAS respectively.

Cropping system shows significant influence (P<0.001) on Leaf Area Index (Figure 8). Maximum LAI was observed in sole soybean (Sb) with 5.3 followed by maize-soybean (MzSb) and sole maize (Mz) with 4.8 and 2.0 respectively. However there was no notable difference in LAI of sole soybean (Sb) and maize-soybean (MzSb). The proportion of incident PAR intercepted by the canopy increased as LAI increased during R1 stage (Figure 9). Despite differences between cropping systems, light interception and LAI maintain strong relationship. LAI of maize-soybean (MzSb) and sole soybean (Sb) exceeded 4 and light interception at that time ranged from 98%-99% but for sole maize (Mz) LAI is less than 3 and light interception was lower than maize-soybean (MzSb) and sole soybean (Sb).

6 b 5 b )

-2 4 m 2 3 a * 2 LAI LAI (m 1 0 Mz Sb MzSb

Treatments

Figure 8. Effect of cropping system on Leaf Area Index (LAI). Where Mz is sole maize, Sb is sole soybean and MzSb is intercropped maize-soybean. Different characters indicate mean differ significantly (P<5 %) with LSD = 0.80 *.

Figure 9. Influence of Leaf Area Index (LAI) on light interception. Where Mz is sole maize, Sb is sole soybean and MzSb is intercropped maize-soybean

6.5. Yield advantage

The result of the field experiment showed no significant difference in maize grain yield between treatments, although a slightly higher yield was obtained in maize-cowpea (MzCp) followed by sole maize (Mz) and maize-soybean (MzSb) respectively (Table 7). There was significantly higher soybean grain yield in sole soybean (Sb) than maize-soybean (MzSb) (Table 7). Cowpea fresh pod yield was also significantly different between cropping systems. Higher cowpea fresh pod yield was obtained in sole cowpea (Cp) than maize-cowpea (MzCp) (Table 7). Soybean and cowpea grain yields were reduced by 44-46% when intercropped with maize.

Table 7. Effect cropping system on yield

Yield (Mg ha-1) Treatments Maize grain Soybean grain Cowpea fresh pod Mz 7.5 - - Sb - 1.7 b - MzSb 7.3 0.9 a - MzCp 7.7 - 3.6 a Cp - - 6.6 b LSD NS 0.15 1.50 Where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize-cowpea and Cp is sole cowpea. Different characters indicate means differ significantly with LSD(P<0.05). NS indicate Non-significant. Maize grain and soybean grain yield (Mg ha-1) adjusted to 15% moisture content. For Maize grain, shelling percentage was based on fresh weight.

While comparing maize grain yield between farms on two different sites (Littregaun and Samaiji), highest and lowest yields were obtained in maize-soybean (MzSb) treatment at farms 3 and 6 with 11.3 Mg ha-1 and 4.4 Mg ha-1 respectively (Figure 10). In all cropping system highest and lowest maize grain yield was obtained on site 1(municipality). For sole soybean (Sb) highest soybean grain yield was observed at farm 5 with 2 Mg ha-1 and lowest at farmer 10 with 1.2 Mg ha-1 on site 1 and site 2 respectively. But for intercropped soybean, the highest and lowest yield was recorded on site 2 with 1.1 Mg ha-1 at farmer 7 and 0.8 Mg ha-1 at farm 11. The highest intercropped cowpea fresh pod yield was obtained at farm 5 with 6 Mg ha-1 and the lowest at farm 8 with 2 Mg ha-1 on site 1 and site 2 respectively. Yields for all the crops were observed highest on site 1 except for intercropped soybean.

Figure 10. Effect of cropping system on crop yields at different farm on two different sites Where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea, VDC refers to Village Development Committee. Maize grain and soybean grain yield (Mg ha-1) adjusted to 15% moisture content. For Maize grain, shelling percentage was based on fresh weight.

The total LER for the intercropping treatment maize-soybean (MzSb) and maize-cowpea (MzCp) were greater than one with 1.54 and 1.68 respectively (Table 8). In both intercropping partial LER for maize was higher than legumes. ATER values were also greater

31 than one in case of intercropping treatment: 1.61 and 1.39 for maize-cowpea (MzCp) and maize-soybean (MzSb) respectively. Both LER and ATER were significantly higher for maize-cowpea (MzCp) than for maize-soybean (MzSb).

Table 8. Effect of cropping system on partial Land Equivalent Ratio, Total Land Equivalent Ratio (LER) and Area Time Equivalent Ratio (ATER) Partial Land Equivalent Ratio (LER) Total Land Area Time Equivalent Equivalent Ratio Treatment Maize Soybean Cowpea Ratio (LER) (ATER) Mz 1 - - 1 1 Sb - 1 - 1 1 MzSb 0.97 0.57 - 1.54 1.39 MzCp 1.23 - 0.45 1.68 1.61 Cp - - 1 1 1 Where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize-cowpea and Cp is sole cowpea

6.6. Stover/biomass DM yield of maize and legumes

Maize stover DM yield was not significantly affected by cropping system (Table 9). However, higher stover DM yield was obtained in sole maize (Mz) followed by maize- soybean (MzSb) and maize-cowpea (MzCp). Soybean stover DM yield was 58% lower in intercropping than the DM yield in sole soybean (Sb) (Table 9). Cropping system did not show any significant influence on cowpea stover DM yield. Furthermore, the analysis revealed that there was no statistical difference in total stover DM yield (including maize and legume) between intercrop and sole maize (Mz).

Table 9. Effect of cropping system on maize-legume stover Dry Matter (DM) yield. Stover DM yield (Mg ha-1) Treatment Maize Soybean Cowpea Total Mz 9.9 - - 9.9 c Sb - 3.8 b - 3.8 b MzSb 9.7 1.6 a - 11.3c MzCp 8.4 - 1.4 9.8 c Cp - - 1.7 1.7 a

LSD P<0.05 NS 0.51 NS 1.69 Where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize-cowpea and Cp is sole cowpea. Different characters indicate means differ significantly with LSD(P<5 %). NS indicate Non-significant.

When comparing different farms between the two sites, the highest maize stover DM yield was observed in maize-soybean (MzSb) with 15. 2 Mg ha-1 at farm 3 and lower with 6.1 Mg ha-1 was observed in maize-cowpea (MzCp) at farm 6 (Figure 11). Both, the highest and the

32 lowest maize stover DM yield was observed on site 1. For soybean, the highest DM stover yield was obtained in sole soybean (Sb) with 5.9 Mg ha-1 at farm 7 on site 2 and the lowest in intercropped soybean with 0.8 Mg ha-1 at farm 6 on site 1. Both, the highest and lowest cowpea stover DM yield was obtained in intercropped cowpea (MzCp) with 2.3 Mg ha-1 and 0.5 Mg ha-1 respectively on site 2 at farm 9 and farm 10 respectively (Figure 11).

Figure 11. Effect of cropping system on maize and legume stover DM yield at different farm on two different sites. Where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea. VDC refers to Village Development Committee.

The results also indicated that the harvest index of maize did not differ between the cropping systems, but for soybean (P=0.028) and cowpea (P=0.043) harvest index was significantly affected by cropping system (Table 10). Higher harvest index was observed in intercropping system for soybean but for cowpea higher was observed in sole rather than intercrop.

Table 10. Effect of cropping system on Harvest Index of maize, soybean and cowpea

Harvest index (HI) Treatment Maize Soybean Cowpea

Mz 0.43 - - Sb - 0.32 a - MzSb 0.43 0.40 b - MzCp 0.48 - 0.73 a Cp - - 0.83 b

LSD 0.05 NS 0.73 0.097 Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea. Different characters indicate means differ significantly (P < 5% ). NS indicate Non-Significant.

6.7. Economic advantage analysis

The result of the partial budget analysis indicated that the lowest total variable cost was recorded in sole soybean (Sb) and the highest was in sole cowpea (Cp). However, the highest net benefit was obtained from maize-cowpea (MzCp) followed by maize-soybean (MzSb), sole maize (Mz), sole cowpea (Cp) and sole soybean (Sb). It is recorded that highest net benefit was obtained from intercropping rather than sole cropping for the three components (Table 11). Net benefit increment was 65% from the lowest net benefit sole soybean (Sb) to the highest net benefit maize-cowpea (MzCp).

Table 11. Net benefit analysis of different cropping system. Treatments Benefits Mz Sb MzSb MzCp Cp

Maize grain yield (kg ha-1) 7,530 - 7,330 7,680 - Soybean grain yield (kg ha-1) - 1,733 964 - - Cowpea fresh pod yield (kg ha-1) - - - 3,570 6,640 Maize value @NRs 25 kg-1 188,250 - 183,250 192,000 - Soybean value @NRS 60 kg-1 - 104,009 57,842 - - Cowpea value @NRs 35 kg-1 - - - 124,950 232,400 Total Value (NRs) 188,250 104,009 241,092 316,950 232,400 Total variable cost (NRs) 82,620 44,803 88,292 150,062 165,503 Net Benefit (NRs) 105,629 59,206 152,800 166,887 66,896 Euro 1 = NRs 121 (NRs = Nepalese Rupees) Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize-cowpea and Cp is sole cowpea.

However, the dominance analysis eliminated sole cowpea (Cp) so that no farmer will choose a farming option that gives lower net benefit with increasing total variable cost (Table 12), while other treatments shows increasing net benefit with increasing total variable cost. The result of marginal rate of return (MRR) analysis (Table 12) revealed that MRR values were greater than 160% only for maize-soybean (MzSb) which were set as the acceptable minimum rate of return for farmers. Shifting of cropping system from sole soybean (Sb) to sole maize (Mz) the MRR was 123% but again shifting cropping system from sole maize (Mz) to maize-soybean (MzSb) it increases by 832%. Intercropping cowpea (MzCp) gives lower MRR (23%) compared to sole maize (Mz) and maize-soybean (MzSb) (Figure 12). Net benefit was higher for maize-cowpea (MzCp) compared to other cropping system (Table 11) but MRR analysis revealed that the return rate is higher in case of maize-soybean (MzSb) than maize-cowpea (MzCp).

Table 12. Marginal rate of return analysis of different cropping system Change in total variable Net Change in Net Total variable Marginal rate of Treatments input cost benefit benefit cost (NRs’000) return (%) (NRs’000 ha-1) (NRs’000) (NRs’000 ha-1)

Sb 45 59 Mz 83 38 106 46 123 MzSb 88 6 153 47 832 MzCp 150 62 167 14 23 Cp 166 15 67 -100 -648 Euro 1 = NRs 121 (NRs = Nepalese Rupees) Where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea.

180 23 % MzCp MzSb

160 ) -1 140 832 % -648 % 120

100 Mz 80 123 % Net benefit (NRs) 60 Cp Sb 40 Net benefit ( '000 NRs ha benefit Net 20 0 0 20 40 60 80 100 120 140 160 180 Total variable input cost ( '000 NRS ha-1)

Figure 12. Net benefit curve of different cropping system.

Euro 1 = NRs 121 (NRs = Nepalese Rupees) where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea.

6.8. Farm characterization and farmer perception

Socioeconomic status of the farmers participating in trial is given in Table 13. Categorization of households was done on the basis of size of land they own. Among 11 farmers, 3 of them are female headed households and rest are male headed.

Table 13. Socioeconomic categorization of participating farmers in study. Marginal Farmer (3)* Small Farmer (2) Medium Farmer (6) Average HH size (#) 4 8 6 Age (Year) 35-60 33-62 45-60 Average land holding (ha) 0.2 0.5 0.7 Livestock Unit (#) 4.7 6.3 7.2 # = number, ha = hectare, HH = Household * Figure within parenthesis indicate number of farmers under each category

In this experimental site, not only heterogeneity in socioeconomic conditions but also crop choice was different between farmers for same growing season during trial period (Figure 13).

80 70 60 50 40 30 Percentage (%) Percentage 20 10 0

Cropping system adopted by farmers

Figure 13. Adoption of different cropping system by farmers in Kharif (rainy) season (Survey report, Victoria, 2014).

Farmers practice sole cropping and intercropping. From Figure 13 it seems that most of the farmers practiced intercropping but by broadcasting and mixing legumes without any row arrangement. Most of farmers grew rice and mixed maize soybean intercropping in the kharif (rainy) season followed by vegetables. Farmers included soybean in their farm either on the field ridges of rice plots, mixed with maize, or even mixed with other legumes. Upland rice and maize seems to be the most grown crops in this location. For maize plantation most of the farmers used local varieties. Different planting time for maize was observed among different farmers. Variability in maize grain yields was observed among different farmers at experimental site under farmers’ practices with an average yield of 2.6 Mg ha-1 (Figure 14).

3.5 3 2.5 2 1.5 1 0.5 Maize grain yield (Mg ha-1) yield grain Maize 0

Participating Farmers

Figure 14. Maize grain yield of local varieties at different farmers field

Maize grain (Mg ha-1) adjusted to 15% moisture content. For Maize grain, shelling percentage was based on fresh weight.

While comparing maize grain yield from farmers practice with the yield obtained from on- farm experiment there was 65% of yield gap (Figure 15). But yield gap between treatment ranges from 2 - 5%. Management practices between the experimental trials were the same; while in farmers plots, farmers were allowed to manage the crops themselves using their own local maize variety.

100

80 65 % Yield gap 60

40 Percent (%) Percent

0 On farm On farm On farm Farmers experiment experiment experiment Practice MzCp Mz MzSb

Figure 15. Yield gap of maize grain yield between different cropping system and farmers practice.

Where MzCp is maize –cowpea, Mz is sole maize and MzSb is maize soybean. 38

Differences in maize grain yield was observed when comparison was made among different farmers categories for same cropping system. Grain yield is comparatively lower in marginal farmer than that of small and medium farmer.(Figure 16).

10.00

9.00 ) -1 8.00 7.00 6.00 Mz 5.00 MzSb 4.00 3.00 MzCp 2.00 Fp Maize grain yield (Mg ha yield grain Maize 1.00 0.00 Marginal Farmer Small Farmer Medium Farmer

Farmer category

Figure 16. Maize yield (Mg ha-1) among different farmer categories in different cropping system and farmers practices. where Mz is sole maize, MzSb is intercropped maize-soybean, MzCp is intercropped maize-cowpea and FP is Farmer’s practice. Maize grain (Mg ha-1) adjusted to 15% moisture content. For Maize grain shelling percentage was based on fresh weight.

In addition to crops, livestock is also a major component of the farming systems in this location, making fodder a concern to every farmer. Farmers walk around 3 to 4 hours to collect forage/fodder leaves and grasses every day. They carry around 25-30 kg of fodder tree leaves and grasses on their back during the rainy season when grass is available (July- November). After this period green grasses become scarce and crop residues are fed from December to April. During scarcity of grasses and tree leaves (April-June) farmers buy, if available, from neighbouring farmers or collect grasses at any other source available, most of the times forced to walk long distances to find the fodder. The livestock units held by farmers in the study site are presented in Table 13, taking in to account that 1 livestock unit (LU) equals to one adult indigenous cow of 250 kg, Ox = 1.2 LU, buffalo = 1.5 LU, goats = 0.1 LU (Hendy et al., 2000). DM feed intake of livestock unit (LU) is estimated based on annual need 39 of 2.28-2.74 Mg DM feed per 250 kg Livestock unit (Kiff et al., 2000). In such case annual DM feed requirement is 10.7, 14.4 and 16.4 Mg DM for marginal, small and medium farmers respectively. Annual DM feed requirement and crops residues (maize and legume stover) production per hectare is shown in Figure 17. This figure indicates that there is large gap in fodder requirement and availability, which has to be fulfilled by other sources, in this case collecting for fodder from trees and communal grasses at long walking distance.

18.00

) 16.00 -1 14.00 ) and annual DM annual ) and

-1 12.00 10.00 8.00 6.00 4.00 requirement (Mg DM 250kg-1 LU requirement 2.00

Total Stover DM yield (Mg DMha Stover yield Total 0.00 Marginal Farmer Small Farmer Medium Farmer

Farmer category

Mz MzSb MzCp FP Annual DM feed requirement

Figure 17. Gap in stover DM yield and annual DM feed requirement among farmer categories on different cropping system and farmer practice. where Mz is sole maize, MzSb is intercropped maize-soybean, MzCp is intercropped maize-cowpea and FP is Farmer’s practice.

Farmers participating and non-participating (neighbouring) in the trials were asked about their view on the practices that were applied in the trial. Different views/opinions were given by different 36 farmers, and are summarized below (Table 14). Out of 36 farmers, 23 were females and rest were males.

Table 14. Farmers’ perspectives on practices applied in the field trial. Why ploughed with mini tiller Why legume intercropped with Why line sowing instead of rather than bullock ? maize? broadcasting?

• Make soil friable (3) • Make soil light (3) • Crop performance (9) • Break clods (2) • Hold soil and protect from soil - Less lodging and high • Crop performance (3) erosion (1) production - better crop health • Legume increase fertility of the - Uniform growth and - good crop emergence soil (6) production of the crops • Less expensive (2) • Green manure from leaves (1) - Healthy crop • Time and labour saving (6) • Increase availability of stover (1) • Intercultural operation (10) • Cut grass and weed (3) • May conserve moisture (2) - Easy for weeding • Can be ploughed by female • Weeding can be done at once for - Easy for fertilizer (8) both crop (2) application - Easy access to field • Uniform ploughing (3) • More benefit from legume than Seed saving and seed sowing • Better than bullock ploughing maize (6) • (1) - Sell in market if excess product at right place (4) Labour saving (1) • Easy to use (4) • Vegetable consumption (7) • Field seems attractive (1) • No need to tame bullock (1) • High production (8) • Land utilization (2) • Not experienced with mini - yield from both crops • tiller (2) - Increase productivity • High production (5) • Land utilization (2) • Maize as staking pole for cowpea

(1)

• Maize flour (1)

• No leaching (2)

Figures in the parenthesis indicate the number of farmers responding to specific question on practices applied in the field trial.

Farmers assessed and ranked the technologies used in the trial based on a scale of 1 and 0 for most preferred and least preferred technology respectively. Ranking was done in the middle of the crop growth period and after harvest. Ranking shows the diversity of perception among the farmers on technologies. Maize-cowpea (MzCp) was mostly preferred before and after harvest (Figure 18). Farmers gave second most preference to maize-soybean (MzSb) after maize cowpea (MzCp) before harvest but its preferences reduced after harvest. For sole maize (Mz) least preference was higher compare to most preference before harvest but after harvest most preference was higher than least preference. Sole soybean (Sb) was the least preferred treatment before and after the harvest. The result on perception showed in Figure 18 is based on the appearance of crops in the field before harvesting and after harvest farmer’s opinion through interview was done for evaluation.

90 80 70 60 50 Mz 40 30 Sb 20 MzSb 10 Percentage (%) Percentage MzCp 0 Most preferred Most preferred after Least preferred Least preferred before harvest harvest before harvest after harvest Scoring by farmers

Figure 18. Farmer’s preference on technologies before and after harvesting. where Mz is sole maize, Sb is sole soybean, MzSb is intercropped maize-soybean, MzCp is intercropped maize- cowpea and Cp is sole cowpea.

7. DISCUSSION 7.1. Crop yield and yield determining factors

The results of the on-farm experiment showed no significant difference in yield parameters (plant height, leaf length, leaf width, active leaf number, girth, grain number per cob) of maize in different cropping systems. This result is similar to the study of Thwala and Ossom (2004) in which no significant difference was found in yield components (plant height, active leaf number per plant and grain number per cob) when maize was intercropped with groundnut and sugar bean. Mburu et al. (2011) reported that in intercrops usually the maize has a competitive advantage over legumes for light and water since they are tall and with larger root system and hence experience limited competition. We observed the same result with no yield difference among cropping systems. In addition to this probably there could be lack of competition for soil nutrients between the maize and legumes. The maize and legume probably extracted nutrients from different zones in the soil profile since they have different rooting depths so competition for nutrient could be minimal. Maximum effective rooting depth for maize, soybean and cowpea as mentioned by Allen et al., (1998) are 1.7 m, 1.3 m and 1.0 m respectively. The crops in the intercropping systems could benefit from the nitrogen fixed by the legume crops. Giller (2001) mentioned this benefit could be due to sparing of soil N rather than direct transfer from the legume. No significant difference in harvest index (HI) of maize was observed between cropping systems (Table 10), which indicates that there was no influence on overall partitioning of assimilates within plants (cf. Mugwe and Mucheru, 2014). This could be the reason for the absence of a significant difference in maize grain yield and stover DM yield between sole and intercrop treatments. Thus in intercropping systems, maize plants respond to the competitive environment by partitioning assimilates within plants in such a way that it balances grain yield and vegetative biomass to have similar harvest index in all cropping systems. In current study yield parameters of soybean (number of nodes, number of branch, branch weight, number of leaves, leaves weight, number of pods per plant) were relatively higher in mono crop compared to intercrop except for plant height. This could be due to shading caused by maize plants. Keating & Carberry (1993) reported that increased far-red: red radiation ratio could result in reduced branching and leaf number at the lower canopy of intercropping system. We observed lower branch and leaf number in soybean when intercropped with maize (Table 5). Tsubo et al., (2001) mentioned that increased LAI can cause higher light interception during vegetative growth. In current study we observed higher LAI with higher

43 light interception in maize-soybean (MzSb) intercropping. However higher LAI often cause no more increase in productivity rather decreases due to respiratory CO2 losses from heavily shaded leaves and stems (Matusso et al., 2014). Our observation on reduced soybean yield in maize-soybean (MzSb) intercropping could be due to shading effect of maize causing reduced photosynthetic rate. Lemma et al., (2009) reported that low irradiance during flowering caused a high proportion of aborted flowers that leads low number of pods per plant in common bean. Climbing nature of cowpea results in less shading in intercropping, hence showing a better competitive ability with maize for light interception. This could be the reason for the absence of a significant difference in cowpea yield parameters (pod length and number of pods per plant) in both sole and intercropping systems (Table 6). Solar radiation not only influences the growth and development of component crops in sole and intercropping cropping system but also the triggering of weed germination. Reducing weed density by crop interference is one of the main causes of yield advantages in intercropping (Poggio, 2005). At 25 DAS component crops were still small and the percentage of ground cover was low. This enabled weed to intercept enough sunlight for germination. As a result there was no significant effect of cropping system on weed density. But at 50 DAS weed density was reduced by the intercropping system (Figure 5). This might be due to ground coverage and interference of light penetration through crop canopy. Increased light exposure to seed with high red: far red ratio leads to increase active form of phytochrome i.e Pfr which triggers seed germination. As a result exposure to red light provides enough Pfr: Pr ratio to trigger germination. But crop interference reduces this ratio and show negative correlation with weed growth (Bilalis et al., 2010). We observed lower weed density in intercropping system than sole maize and sole soybean. Major weed species observed in this study belongs to different families with different growth habits and morphological characteristics. However, particular weed characteristics were not studied in this experiment; dissimilar trend between weed density and weed fresh biomass in cropping system could be due to different weed species suppressed by different crops.

7.2. Yield advantage and economic benefits

Higher LER and ATER in intercropping systems in this study indicated that component crops share available resources in an effective manner over time and space. This could be due to differences in morphological and physiological characteristics among intercrop components, which could allow them to occupy different niches. Different growth period implies resource requirement and active growth at different times and do not show intense competition with

44 each other (Fukai and Trenbath, 1993). Similar results with LER of 1.68 in maize-soybean intercropping were observed by Undie et al (2012). Tariah & Wahua (1985) and Tsubo et al., (2004) also reported increased yield in intercropping with maize-cowpea and maize-bean. Similar to the current study an ATER value greater than one (1.48) in maize bean intercropping has been reported by Pandita et al. (2000). LER and ATER in the current study revealed different values for same intercropping system i.e. higher in LER and lower in ATER. An ATER value lower in case of intercropping may be due to development of temporal as well as spatial complementary whereas in case of LER only spatial arrangement is considered. Besides land productivity maize-based intercropping systems resulted in higher net benefit than sole cropping of maize due to additional income derived from yield of intercropped legume crops. Economic analysis results indicated higher net benefit in maize-cowpea (MzCp) intercropping than sole maize (Mz) (Table 11). But from marginal analysis higher return benefit (832%) is obtained in maize-soybean (MzSb) than sole maize (Mz) (Table 12). This could be due to the influence of additional prices of soybean grain that results 30% increment in net benefit. In addition variable cost for fertilizer was reduced in maize-soybean (MzSb) compare to sole maize. Hence only 6 % of total variable cost was increased resulting most profitable cropping system.

7.3. Farmers’ perspectives and preferences

Farmers’ perspectives and preferences on technology and cropping systems (Table 14 and Figure 18) do not necessarily mean that farmer would adopt the cultivation practices. However, the ranking was particularly helpful for farmers to elite the most likely treatments from the trial. Farmer evaluation of technologies and what they perceived as good in their circumstances highlighted their socio-economic status. Farmers did not have knowledge and experience about the technology like mini tiller tractor and line sowing. Hence most of the farmers’ responses to these technologies (Table 14) were based on direct observation at the time of field preparation and field visit. Farmers indicated that the mini tiller technology was easy to operate by female (female can use this technology), and it would be time and labour saving. In this study zone female farmers do most of the agricultural activities (FYM application, planting, weeding), except for ploughing, which is done by male. In most of the households, males are out migrated for seasonal jobs. In such case, if the return of the male household members has been delayed during the planting season then labour has to be hired for ploughing. As a result production cost increases. If labour is unavailable or not affordable

45 they have to delay planting, which is also one of the reasons that different farmers have different maize planting dates. This could be the reason for the appreciation of the usefulness of the mini tiller for ploughing. In addition, the majority of the respondents were female farmers. Though mini tillers can be operated by females, this could also lead to additional workload for female farmers. Easy availability (transportation problem) and accessibility (economic support like subsidy) of such farm machinery to remote communities is also a major concern. Further cost benefit analysis should be done for use of such technology as some farmers mentioned it as less expensive and to use it rather than to tame bullock. Food sufficiency is the major priority of the farmers in this location. So farmers’ reflection on legume integration was mainly on yield obtained from both crop components. Legume can also be used for vegetable consumption and income from sale of the legume product (soybean, cowpea). Therefore, the farmers’ ranking of the treatment used in the current study (Figure 18) showed that the most preferred technology was maize-cowpea (MzCp) followed by maize-soybean (MzSb). Stover yield obtained from maize and legume could also be the reason for the preference on intercrop because stover of both crops is used as fodder for livestock. For maize-soybean (MzSb), most preference was reduced after harvest because soybean plants were much suppressed by maize plant in intercropping affecting yield components of legume. Farmers’ response on improvement in soil fertility by legume integration could be due to awareness program raised by different organization on soil management in that location. However farmers were not able to quantify the improvement of soil fertility except for soil structure responding that soil become friable if legume integrated. Most of the farmers use local maize varieties yielding mostly one cob per plant. But in current study on average two cobs per plant were observed in hybrid maize. In addition number of plant retaining on plot was higher as compared to local varieties. This could be the reason for responding by majority of farmers on better crop growth performance in line sowing. After experience shared by participating farmers in the trial at the time of field visit and direct field observation by non-participating (neighbour) farmers, most of them reflected that it is easy for intercultural operation (weeding, fertilizer application) in line sowing.

7.4. Yield variability among farms

Crop production is based upon traditional practices such as the use of local (low yielding) varieties and seed broadcasting. There are differences in plant population per square meter due to different seeding rates together with different management practices among farmers. Nutrient demand of crop is fulfilled by FYM, which is not enough because it is poorly

46 managed, mostly with open storage system resulting in large nutrient losses. FYM prepared by farmers in open storage system comprises 0.6%, 0.3% and 0.4% of NPK respectively (Chapagain and Gurung, 2010). In addition soil nutrient content is also different among farmers (Table 1). Variability in crop yields within and across the farms is influenced by soil fertility gradient, due to inherent variability in soil types in landscape and differential allocation of nutrient in the field (Tittonell et al., 2013), together with crop management practices (planting dates, FYM application) (Tittonell et al., 2008). Other factors are also responsible for yield differences like biological (soil moisture, pest, birds and animal damage), socioeconomic (land holding, livestock unit, age, household number); farmers’ knowledge and experience; decision making and institutional support. These factors can cause for difference in maize grain yield among farmers in experimental site under farmer’s practices (Figure 14). Even in the on-farm trial of the current study some differences can be seen in crop biomass (grain and stover) yield among the farmers (Figure 10 and 11) though management practices (seeding date, weeding, fertilizer application) were the same for all farms. This might be due to difference in past land use history like FYM application, crop choice and crop rotation practiced by different farmers in their field. As a result, differences in soil fertility, soil productivity, nutrient balance and resource use efficiency can occur and result in the differences on economic and biological yield of crops among farmers. Tittonell et al. (2008) reported that farmers management decisions and soil variability can be highly variable affecting resource use efficiencies within and across heterogeneous farms. There were also differences in plant population stand on plots which was due to poor germination and maize plant lodging (bending of the stalk of the plant). Not only at individual farmer level but also at three different farm typologies, maize grain and stover DM yields variability were observed in this study and in farmer’s practices as well (Figure 16 and Figure 17). This could be due to the decision making of the farm on crop choices for plantation on available land. Small and medium farms might have more interest to grow legume crops like soybean as a sole or mixed with cereal crops on some part of the field for income earning through sale in the local market. But for marginal farmers food sufficiency might be the priority and they do not have enough land for sole legume plantation. Even if mixed with cereals, legume plant proportion will be very less as they do not want to decrease the major staple food plant population. In such case soil fertility gradient might occur between farm typology due to integration of legume in cropping system. Also the livestock unit difference within the farm typology, lower in marginal farmer as compared to small and middle farmer (Table 13), could be the reason as 47 livestock is only main source of manure that contribute nutrient availability for crop. Lower livestock unit results in lower quantity of FYM that might not be enough for soil rehabilitation. In addition most of the time livestock are allowed for open grazing resulting FYM outgoing from the farming system. Den Haan et al. (1997) reported that six livestock units are needed to provide sufficient FYM for one year to grow one hectare of rice-maize- wheat in Nepal. But in current situation required quantity of manure is not available because of two reasons; first, out grazing leads to partial collection in shed and second, collected FYM is inefficient due to poorly managed open storage system

7.5. Practical implications

Huge yield gap in maize grain between on-farm trial and farmer’s practices presented in Figure 15 might be due to crop variety performance between local and hybrid varieties. This could be one of the factors to be improved as current study has shown that hybrid maize could perform better in terms of yield and income even in marginal production environment. In order to exploit the potential of hybrid maize it is necessary to apply an optimum level of fertilizer; otherwise, it shows poor performance on soils with low nitrogen level because they have been developed in research station under optimum nitrogen conditions (Nyoro, 2002). However there are different economic and social factors that affect for the adoption of hybrid maize varieties. Farmers in this zone do not apply minerals fertilizer in their field except for those who do vegetable farming because of high price of minerals fertilizers. In addition price of hybrid maize is also higher as compared to improved (open pollinated) maize. Seed saving from local varieties for next season is common practice in this zone which is not possible for hybrid varieties. Local varieties usually have short growth periods and are harvested early but hybrid varieties tend to have longer growing periods, so there is more risk of crop damage by livestock, birds, pest and disease if only one farmer adopt a long period variety, while the rest have already harvested their maize. Better taste and ease for shelling is also another factor that makes farmer more attachment with local varieties. Numerous biophysical and socio economic constraints have to be addressed in order for a technology to fit in to the system and generate impact (Ojiem et al., 2006). Plant population per hectare was 20% lower in farmers practice as compared to on-farm trial which could be the second reason for huge yield gap. In current study row spacing was maintained in such a way that leads to accommodate maximum maize plant population together with legume integration in intercropping system. There was no significant difference on maize yield between sole maize and intercropping providing enough space for effective

48 resource utilization. Here integrating legume with maize shows economic benefit together with yield advantage as shown by higher LER and ATER than sole cropping. In addition incorporating legumes in a cropping system can increase nutrient availability because of their ability to fix nitrogen from the atmosphere and that can be utilized by cereal crops. Allison (1992) reported that potential of biological N from legume for non- legume crops like maize and rice are more important than their potential as food or cash crops. Crop residues from arable cultivation are used as animal feed and bedding material. Livestock production is well below its full potential because of severe feed shortages in the dry season. Despite no significant difference in total stover DM yield, 8% extra fodder is gained from maize-soybean (MzSb) as compared to sole maize (Mz) (Table 9). It is difficult to fulfil annual DM feed requirement with farmers yield hence change in cropping system could be helpful if both maize and legume stover are contributed as fodder, where 50-60 % more stover DM yield can be obtained as compared to farmer practice (Figure 17). But for intercropping with maize, legume variety selection should be focused in determining minimum intercrop competition and maximum complementary between component crops. Due to semi determinant nature of soybean variety used in current study, it was more susceptible to shading environment which results in poor growth and yield performance. Another important thing to be considered is that farmer perceived legume integration as a commodity for household consumption and income generating rather than benefit for soil fertility which is clear from farmer’s perspective (Table 14). So other parallel benefit should be visualized like weed suppression, animal feed, suitability/compatibility in intercropping system and additional grain yield for food for quick acceptance of legume integration. Higher price of hybrid maize seed hinder to be used by small farmers but should go for improved varieties as farmers can afford it and even save seed for next season which in not possible in hybrid maize seed. Existing practices need some changes in the production factor to have practical implication in farmer’s fields to improve productivity which is shown in Table 15. Awareness should be raised to the farmers to shift their production technology. Above all, the participatory approach will be more effective for technology verification and dissemination to farmers through demonstrative research.

Table 15. Shift in production factors Practical implication Factors Shift Benefit Major concerns

Production factors

Conserve soil properties Land preparation Manual and bullock to Easily accessible and and soil moisture, time mini tiller mobility saving

Increased yields, resistant Meet farmers demand, Local to to pest, disease, shading, easily available and Variety Improved/hybrids complementary effect, affordable, initial subsidy varieties higher biomass

Efficient resource Knowledge sharing to Crop arrangement Broadcasting to row utilization, Plant farmers, adoption of arrangement population can be certain techniques maintained

Less fertilizer cost, better Farmers education, Improve FYM Nutrient management quality of soil, biological adoption of certain management, nitrogen fixation, higher techniques Legume integration biomass than sole

Less technical knowledge Knowledge transfer and Centralized to Timely service and client of service provider input support decentralized (NGOs, oriented Subsidy for inputs leader farmers)

8. CONCLUSION

The objective of this research was to evaluate the effect of maize-legume intercropping on productivity of maize and legume on maize based farming system on the mid hills of Nepal. This study was mainly focused on the crop component of the system. To some extent this study revealed intercropping together with row arrangement have benefit on efficient resource utilization like moisture, light interception and land utilization. Maize grain yield and stover DM yields were not affected by any of the cropping system showing strong competitive ability of maize in mixtures with legumes. Legume yields were highly reduced by maize standing in intercropping system. Intercropping maize with legumes showed advantages in land use efficiency as compared to sole cropping as indicated by LER and ATER. Economic superiority and positive farmers perception was also observed for maize-legume intercropping compared to sole cropping. The yield gap in maize grain and stover between on-farm trial and farmers’ practices was attributed to differences in management practice like seed types (local or hybrid), row arrangement, plant population and mineral fertilizer application. There is still a need to shift in production factors to lower the yield gap and to eliminate the knowledge gap to allow profitable and productive implementation of intercropping systems in practice.

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10. APPENDIX

i. Gantt chart for measuring different parameter during on farm trial.

Parameter measured Days After Sowing in field Maize Plant 22 25 30 37 44 50 51 60 62 66 67 69 73 74 76 80 90 97 104 110 130 Plant height

Leaf length

Leaf width

Active leaf

R1 stage

Leaf Area Index

Maize grain per cob Maize grain yield measurement Maize stover yield measurement

Plant girth

Soybean Plant Plant height Number of nodes per plant Number of branch per plant Number of leaves per plant

Branch fresh weight

Leaves fresh weight

Leaf Area Index Number of pods per plant Soybean grain yield measurement Soybean stover yield measurement

Cowpea Plant Cowpea fresh pod yield

Cowpea pod length Cowpea stover yield measurement

PAR measurement

Weed sampling Weed density

Weed fresh weight

58 ii. Maize plant height on different cropping system

Maize Plant Height (cm) Farmers (Block) Treatment 22 30 37 44 51 62 76 DAS DAS DAS DAS DAS DAS DAS Harvest Farmer 1 Mz 14.53 28.58 57.83 95.67 167.50 261.17 292.33 299.40 Farmer 2 Mz 13.50 24.33 48.17 82.33 151.83 245.50 293.83 297.30 Farmer 3 Mz 19.83 40.83 69.50 127.17 199.00 269.50 308.83 329.90 Farmer 4 Mz 18.00 45.17 65.00 125.83 160.17 301.17 305.83 316.70 Farmer 5 Mz 16.50 30.25 47.33 84.50 149.33 239.17 292.50 321.70 Farmer 6 Mz 17.75 35.58 63.50 105.67 165.00 274.33 314.67 314.70 Farmer 7 Mz 12.75 24.67 41.83 61.67 95.50 211.17 248.83 270.00 Farmer 8 Mz 21.58 38.17 54.83 79.00 128.33 259.67 272.67 284.00 Farmer 9 Mz 21.17 32.50 56.67 90.83 130.83 245.00 285.33 295.00 Farmer 10 Mz 15.00 31.67 48.33 88.00 119.00 267.33 306.17 306.50 Farmer 11 Mz 24.33 43.33 65.50 95.33 144.17 252.67 257.83 288.50 Farmer 1 MzSb 13.72 32.33 62.83 120.83 183.83 290.83 302.17 311.30 Farmer 2 MzSb 13.08 28.83 53.33 100.00 170.67 265.80 300.33 295.09 Farmer 3 MzSb 19.67 41.67 79.00 146.50 228.00 280.50 320.50 316.00 Farmer 4 MzSb 21.50 41.50 73.50 133.50 169.17 313.17 322.83 327.10 Farmer 5 MzSb 12.67 30.83 50.83 97.17 163.00 270.00 313.33 299.50 Farmer 6 MzSb 16.50 31.17 55.00 85.17 126.42 200.17 271.17 306.50 Farmer 7 MzSb 15.17 29.33 48.33 68.33 109.67 213.17 240.33 279.50 Farmer 8 MzSb 24.75 36.67 57.83 83.67 133.00 259.67 275.17 288.50 Farmer 9 MzSb 23.08 41.17 64.17 99.50 148.00 274.17 282.17 308.70 Farmer 10 MzSb 18.33 32.33 52.83 93.17 115.67 236.50 289.83 285.17 Farmer 11 MzSb 27.83 48.83 75.33 105.67 162.00 293.60 295.33 285.20 Farmer 1 MzCp 16.70 31.33 53.33 110.67 183.33 287.00 302.67 295.70 Farmer 2 MzCp 17.17 37.67 57.33 107.33 178.00 270.50 312.20 282.00 Farmer 3 MzCp 19.00 40.17 76.50 141.00 219.00 303.33 309.33 318.50 Farmer 4 MzCp 17.17 37.67 66.85 117.83 153.33 238.67 294.33 303.50 Farmer 5 MzCp 13.00 29.50 47.67 95.33 152.83 272.00 307.00 303.80 Farmer 6 MzCp 16.67 28.00 58.25 77.67 118.42 196.33 262.00 283.40 Farmer 7 MzCp 15.83 33.83 49.67 69.17 121.00 233.33 273.00 253.50 Farmer 8 MzCp 20.83 38.17 61.17 86.83 137.83 268.50 290.50 292.00 Farmer 9 MzCp 26.33 43.00 60.83 96.00 135.83 246.17 272.83 298.20 Farmer 10 MzCp 17.42 33.50 51.50 91.83 121.33 249.33 300.00 313.10 Farmer 11 MzCp 22.92 50.33 77.83 106.50 155.33 265.20 286.17 280.00

59 iii. Maize leaf length and girth size of different cropping system

Plant girth Average Leaf length (cm) (cm) Farmers (Block) Treatment 22 30 37 44 51 62 76 Harvest DAS DAS DAS DAS DAS DAS DAS Farmer 1 Mz 6.65 13.26 27.42 55.25 72.25 97.00 92.33 51.00 Farmer 2 Mz 6.40 11.09 28.58 48.17 74.33 87.25 90.00 43.17 Farmer 3 Mz 6.55 20.75 44.50 61.25 80.17 98.83 89.00 53.08 Farmer 4 Mz 6.90 22.70 42.00 60.83 79.67 95.50 90.33 49.92 Farmer 5 Mz 7.30 14.13 31.00 50.00 72.33 86.92 95.42 41.67 Farmer 6 Mz 5.40 19.88 39.25 60.83 85.00 106.83 105.33 45.23 Farmer 7 Mz 6.65 10.42 29.91 45.58 62.67 82.17 98.75 51.17 Farmer 8 Mz 6.65 20.88 42.58 58.17 69.00 88.50 92.25 43.17 Farmer 9 Mz 5.70 20.00 37.67 55.55 71.55 90.00 84.50 43.17 Farmer 10 Mz 5.45 15.04 33.75 51.25 70.00 94.67 95.92 44.50 Farmer 11 Mz 6.75 23.38 42.18 62.09 74.18 94.00 86.08 48.17 Farmer 1 MzSb 7.00 14.09 36.58 58.08 76.00 98.67 87.50 57.42 Farmer 2 MzSb 6.70 14.18 32.58 50.36 76.00 86.50 95.83 50.58 Farmer 3 MzSb 6.40 24.53 45.79 67.67 86.08 104.50 90.83 59.82 Farmer 4 MzSb 6.50 24.75 45.83 68.25 82.17 98.00 88.17 53.58 Farmer 5 MzSb 5.50 12.92 28.83 52.08 75.33 89.83 94.58 45.33 Farmer 6 MzSb 5.45 16.10 35.00 58.50 78.33 100.42 97.33 38.67 Farmer 7 MzSb 5.65 17.55 33.73 48.10 66.40 84.83 96.92 56.75 Farmer 8 MzSb 6.65 23.82 36.80 53.80 65.00 88.67 89.42 49.92 Farmer 9 MzSb 5.40 26.38 47.27 65.67 82.67 97.17 85.67 47.33 Farmer 10 MzSb 6.65 14.87 36.42 55.33 77.25 95.50 91.42 49.17 Farmer 11 MzSb 6.40 28.77 51.67 67.33 79.33 100.67 84.10 50.58 Farmer 1 MzCp 6.50 16.50 32.67 55.00 74.67 89.00 87.50 51.58 Farmer 2 MzCp 6.14 17.04 35.75 57.90 81.00 92.33 101.67 49.50 Farmer 3 MzCp 7.70 20.12 44.42 68.50 84.17 93.83 85.50 61.75 Farmer 4 MzCp 6.30 21.80 38.71 57.00 79.00 94.83 89.00 48.92 Farmer 5 MzCp 5.50 13.17 33.00 52.55 73.17 87.50 98.21 44.67 Farmer 6 MzCp 4.55 14.42 31.64 50.50 75.83 118.42 99.67 43.67 Farmer 7 MzCp 5.86 20.20 37.00 52.75 70.17 84.50 96.08 44.25 Farmer 8 MzCp 7.25 19.45 37.09 61.91 73.09 91.33 80.75 45.42 Farmer 9 MzCp 5.27 25.88 45.75 63.25 80.00 96.67 88.00 40.50 Farmer 10 MzCp 5.90 15.89 35.67 55.50 74.83 94.33 96.08 43.08 Farmer 11 MzCp 6.20 25.79 47.83 70.08 82.83 100.18 75.20 37.75

iv. Maize leaf width on different cropping system

Average Leaf width (cm) Farmers (Block) Treatment 22 DAS 30 DAS 37 DAS 44 DAS 51 DAS 62 DAS 76 DAS Farmer 1 Mz 1.91 3.05 6.17 8.76 10.93 10.07 5.93 Farmer 2 Mz 1.39 2.77 5.38 8.87 10.43 9.50 6.06 Farmer 3 Mz 2.09 4.48 7.26 9.91 10.75 10.30 5.41 Farmer 4 Mz 2.29 4.50 7.33 9.80 11.09 9.83 5.49 Farmer 5 Mz 1.46 3.38 6.15 8.18 9.68 9.36 4.45 Farmer 6 Mz 1.77 3.53 5.84 8.15 9.80 9.75 5.96 Farmer 7 Mz 1.50 3.45 5.68 7.63 9.72 11.25 7.42 Farmer 8 Mz 2.19 4.68 6.87 8.38 10.42 10.76 5.83 Farmer 9 Mz 1.97 3.68 6.03 7.52 9.30 9.49 6.08 Farmer 10 Mz 1.69 3.24 5.44 7.18 9.60 11.14 6.21 Farmer 11 Mz 2.28 4.30 6.65 8.15 9.72 9.77 7.67 Farmer 1 MzSb 1.72 3.58 6.42 9.13 10.73 9.25 6.21 Farmer 2 MzSb 1.66 3.18 6.09 9.92 11.42 10.80 5.52 Farmer 3 MzSb 2.36 4.72 7.63 10.70 12.20 10.42 6.46 Farmer 4 MzSb 2.27 4.76 8.13 9.45 10.90 9.68 5.86 Farmer 5 MzSb 1.52 3.32 6.23 8.67 10.17 9.90 4.98 Farmer 6 MzSb 1.70 2.93 4.91 7.20 8.50 9.17 5.73 Farmer 7 MzSb 2.21 3.79 5.73 7.79 9.82 11.34 7.42 Farmer 8 MzSb 2.53 4.57 7.11 8.60 10.72 10.03 6.25 Farmer 9 MzSb 2.46 4.27 6.33 7.88 9.13 9.90 6.72 Farmer 10 MzSb 1.49 3.82 5.70 7.73 8.70 9.68 6.54 Farmer 11 MzSb 2.78 5.22 6.96 8.48 10.87 9.78 7.75 Farmer 1 MzCp 1.84 3.52 6.48 9.51 10.42 8.87 6.00 Farmer 2 MzCp 1.92 3.51 6.42 9.13 10.62 10.45 5.28 Farmer 3 MzCp 2.05 4.30 8.48 10.53 12.42 10.25 6.61 Farmer 4 MzCp 2.23 4.18 7.56 9.10 10.60 9.88 5.42 Farmer 5 MzCp 1.48 3.49 6.38 9.13 10.47 10.78 4.57 Farmer 6 MzCp 1.48 2.70 4.45 6.65 8.68 8.78 6.71 Farmer 7 MzCp 2.27 4.42 6.21 8.25 10.12 10.82 6.33 Farmer 8 MzCp 2.22 3.73 6.82 8.27 10.15 8.73 5.92 Farmer 9 MzCp 2.58 4.33 5.99 7.50 8.82 8.83 5.79 Farmer 10 MzCp 1.68 3.33 5.27 7.32 8.63 9.76 5.92 Farmer 11 MzCp 2.54 4.84 7.63 9.22 10.15 9.29 6.58

61 v. Maize active leaf on different cropping system

Maize Active leaf (#) Grains Farmers (Block) Treatment per cob 60 DAS 67 DAS 74 DAS 90 DAS 97 DAS 104 DAS Harvest Farmer 1 Mz 11 15 15 13 11 11 615 Farmer 2 Mz 11 14 15 13 12 12 594 Farmer 3 Mz 13 15 15 13 12 12 600 Farmer 4 Mz 12 16 16 14 13 12 685 Farmer 5 Mz 10 14 15 13 12 12 656 Farmer 6 Mz 12 15 15 14 13 12 593 Farmer 7 Mz 9 13 14 12 10 10 569 Farmer 8 Mz 11 14 14 13 12 11 585 Farmer 9 Mz 11 15 13 12 11 10 548 Farmer 10 Mz 11 16 15 14 13 13 631 Farmer 11 Mz 11 13 13 12 11 11 619 Farmer 1 MzSb 11 15 14 12 11 11 632 Farmer 2 MzSb 11 15 15 13 11 11 657 Farmer 3 MzSb 13 16 15 14 13 12 593 Farmer 4 MzSb 11 16 16 13 13 12 610 Farmer 5 MzSb 11 15 14 12 11 11 597 Farmer 6 MzSb 11 14 15 14 13 13 609 Farmer 7 MzSb 10 13 13 12 11 11 548 Farmer 8 MzSb 11 14 14 13 12 12 630 Farmer 9 MzSb 11 14 13 12 10 10 557 Farmer 10 MzSb 10 14 14 13 11 10 608 Farmer 11 MzSb 13 15 15 13 12 12 563 Farmer 1 MzCp 11 15 14 12 11 11 638 Farmer 2 MzCp 10 15 14 12 12 12 542 Farmer 3 MzCp 12 15 14 13 13 13 641 Farmer 4 MzCp 10 15 15 13 13 12 552 Farmer 5 MzCp 10 15 14 12 12 11 610 Farmer 6 MzCp 10 13 13 12 12 12 555 Farmer 7 MzCp 10 13 15 13 12 12 576 Farmer 8 MzCp 11 14 14 13 13 12 634 Farmer 9 MzCp 11 13 12 11 10 10 599 Farmer 10 MzCp 10 15 15 14 13 13 552 Farmer 11 MzCp 13 14 14 13 12 12 522

vi. Soybean yield parameter

leaves Farmers Height Branch weight #pods/ Treatment # Nodes # Branch # leaves weight (Block) (cm) (gram) plant (gram) Farmer 1 Sb 108.33 37 8 146.67 142 76.70 82 Farmer 2 Sb 113.50 52 8 160.00 158 95.00 70 Farmer 3 Sb 169.00 75 7 155.00 286 170.00 81 Farmer 4 Sb 120.00 44 7 130.00 136 90.00 74 Farmer 5 Sb 132.50 42 6 140.00 128 85.00 73 Farmer 6 Sb 146.33 47 4 136.67 150 76.67 87 Farmer 7 Sb 127.50 45 8 105.00 115 65.00 81 Farmer 8 Sb 142.50 26 4 80.00 69 50.00 * Farmer 9 Sb 105.00 47 7 110.00 139 80.00 82 Farmer 10 Sb 105.00 38 6 55.00 111 50.00 56 Farmer 11 Sb 112.50 45 5 165.00 122 80.00 71 Farmer 1 MzSb 162.67 15 3 53.30 52 33.30 74 Farmer 2 MzSb 182.50 19 3 40.00 63 45.00 77 Farmer 3 MzSb 188.50 33 6 120.00 122 75.00 63 Farmer 4 MzSb 200.00 21 2 50.00 63 50.00 60 Farmer 5 MzSb 185.00 21 2 45.00 59 45.00 55 Farmer 6 MzSb 204.00 20 3 40.00 67 33.33 23 Farmer 7 MzSb 134.00 21 2 60.00 66 40.00 84 Farmer 8 MzSb 142.50 15 3 40.00 45 30.00 * Farmer 9 MzSb 80.00 18 3 15.00 57 45.00 26 Farmer 10 MzSb 95.00 9 1 17.50 26 15.00 40 Farmer 11 MzSb 130.00 28 4 60.00 91 45.00 33

vii. Cowpea yield component

Farmers (Block) Treatment Fresh weight (t/ha) Avg pod length (cm) No. of pods/plants

Farmer 1 MzCp 3.39 37.75 6.1 Farmer 2 MzCp 3.14 39.10 5.9 Farmer 3 MzCp 3.03 37.98 5.8 Farmer 4 MzCp 2.81 35.26 4.6 Farmer 5 MzCp 6.10 42.88 5.3 Farmer 6 MzCp 3.57 40.68 6.5 Farmer 7 MzCp 4.91 42.86 5.2 Farmer 8 MzCp 2.06 42.65 6.7 Farmer 9 MzCp 4.87 40.40 8.0 Farmer 10 MzCp 3.08 36.18 7.1 Farmer 11 MzCp 2.43 42.12 6.3 Farmer 1 Cp - - - Farmer 2 Cp 6.48 40.08 6.3

Farmers (Block) Treatment Fresh weight (t/ha) Avg pod length (cm) No. of pods/plants

Farmer 3 Cp - - - Farmer 4 Cp - - - Farmer 5 Cp - - - Farmer 6 Cp - - - Farmer 7 Cp - - - Farmer 8 Cp 4.85 40.55 4.6 Farmer 9 Cp - - - Farmer 10 Cp - - - Farmer 11 Cp - - -

viii. Light interception on different cropping system

Light Interception % Farmers (Block) Treatment

60 DAS 67 DAS 74 DAS 90 DAS 97 DAS Farmer 1 Mz 96 84 93 92 73 Farmer 2 Mz 97 91 86 94 76 Farmer 3 Mz 92 89 92 90 72 Farmer 4 Mz 97 94 92 94 79 Farmer 5 Mz 91 91 89 82 77 Farmer 6 Mz 95 84 94 92 82 Farmer 7 Mz 87 94 94 83 75 Farmer 8 Mz 94 93 93 81 77 Farmer 9 Mz 96 96 94 73 73 Farmer 10 Mz 94 95 92 83 92 Farmer 11 Mz 85 92 96 89 90 Farmer 1 Sb 99 100 100 99 98 Farmer 2 Sb 99 99 100 100 99 Farmer 3 Sb 99 100 99 99 98 Farmer 4 Sb 99 99 100 100 98 Farmer 5 Sb 99 99 99 99 98 Farmer 6 Sb 97 98 99 100 100 Farmer 7 Sb 94 100 100 100 99 Farmer 8 Sb 100 100 100 100 100 Farmer 9 Sb 59 69 98 99 98 Farmer 10 Sb 87 91 97 99 99 Farmer 11 Sb 99 100 100 100 99 Farmer 1 MzSb 99 96 99 98 98 Farmer 2 MzSb 98 96 96 98 96 Farmer 3 MzSb 99 99 100 99 98 Farmer 4 MzSb 100 99 99 99 98 Farmer 5 MzSb 99 98 99 99 98

Light Interception % Farmers (Block) Treatment 60 DAS 67 DAS 74 DAS 90 DAS 97 DAS Farmer 6 MzSb 97 98 99 99 97 Farmer 7 MzSb 99 100 100 99 98 Farmer 8 MzSb 100 100 99 96 99 Farmer 9 MzSb 98 99 97 96 91 Farmer 10 MzSb 96 96 96 98 95 Farmer 11 MzSb 99 99 99 98 99 Farmer 1 MzCp 99 99 96 94 81 Farmer 2 MzCp 100 97 98 92 85 Farmer 3 MzCp 99 99 97 95 82 Farmer 4 MzCp 100 98 98 96 83 Farmer 5 MzCp 100 99 98 96 85 Farmer 6 MzCp 99 97 98 90 88 Farmer 7 MzCp 100 99 98 88 81 Farmer 8 MzCp 99 99 98 84 92 Farmer 9 MzCp 99 99 91 94 72 Farmer 10 MzCp 98 96 97 81 87 Farmer 11 MzCp 99 91 97 84 81 Farmer 1 Cp - - - - - Farmer 2 Cp 99 98 98 87 80 Farmer 3 Cp - - - - - Farmer 4 Cp - - - - - Farmer 5 Cp - - - - - Farmer 6 Cp - - - - - Farmer 7 Cp - - - - - Farmer 8 Cp 100 99 99 86 79 Farmer 9 Cp - - - - - Farmer 10 Cp - - - - - Farmer 11 Cp - - - - -

ix. Leaf Area Index of different cropping system

Leaf Area Index Farmers (Block) Treatment R1 stage Farmer 1 Mz 1.84 Farmer 2 Mz 1.78 Farmer 3 Mz 2.36 Farmer 4 Mz 2.52 Farmer 5 Mz 1.75 Farmer 6 Mz 2.36 Farmer 7 Mz 1.55 Farmer 8 Mz 2.14

Leaf Area Index Farmers (Block) Treatment R1 stage Farmer 9 Mz 1.71 Farmer 10 Mz 2.05 Farmer 11 Mz 2.01 Farmer 1 Sb 5.67 Farmer 2 Sb 6.22 Farmer 3 Sb 6.99 Farmer 4 Sb 5.71 Farmer 5 Sb 5.81 Farmer 6 Sb 7.16 Farmer 7 Sb 5.50 Farmer 8 Sb 3.42 Farmer 9 Sb 4.93 Farmer 10 Sb 2.71 Farmer 11 Sb 4.35 Farmer 1 MzSb 3.98 Farmer 2 MzSb 4.05 Farmer 3 MzSb 8.00 Farmer 4 MzSb 6.03 Farmer 5 MzSb 4.30 Farmer 6 MzSb 5.74 Farmer 7 MzSb 4.61 Farmer 8 MzSb 4.94 Farmer 9 MzSb 3.60 Farmer 10 MzSb 2.89 Farmer 11 MzSb 5.15

x. Weed density and weed fresh weight on different cropping system

Weed density (#) Weed FW (gram/0.25 sq meter) Farmers (Block) Treatment

25 DAS 50 DAS 25 DAS 50 DAS Farmer 1 Mz 107 177 8.5 225 Farmer 2 Mz 90 195 4 118 Farmer 3 Mz 87 240 8 256 Farmer 4 Mz 94 203 4.5 97 Farmer 5 Mz 116 228 4 97 Farmer 6 Mz 224 87 17 154 Farmer 7 Mz 53 95 8.5 143 Farmer 8 Mz 108 195 33.5 119 Farmer 9 Mz 197 294 26 125 Farmer 10 Mz 25 83 5.5 134 Farmer 11 Mz 81 189 21.5 215 66

Weed density (#) Weed FW (gram/0.25 sq meter) Farmers (Block) Treatment

25 DAS 50 DAS 25 DAS 50 DAS Farmer 1 Sb 167 43 7 336 Farmer 2 Sb 101 118 3.5 448 Farmer 3 Sb 104 108 9.5 102 Farmer 4 Sb 79 263 5.5 185 Farmer 5 Sb 99 185 10.5 65 Farmer 6 Sb 183 82 16.5 305 Farmer 7 Sb 50 120 11.5 102 Farmer 8 Sb 106 163 18.5 165 Farmer 9 Sb 234 107 35 185 Farmer 10 Sb 43 104 6.5 122 Farmer 11 Sb 168 174 39.5 89 Farmer 1 MzSb 186 47 7.5 356 Farmer 2 MzSb 109 93 6 143 Farmer 3 MzSb 88 75 6.5 65 Farmer 4 MzSb 152 201 6.5 70 Farmer 5 MzSb 104 104 8.5 30 Farmer 6 MzSb 147 52 14 89 Farmer 7 MzSb 86 50 9 256 Farmer 8 MzSb 114 143 24 143 Farmer 9 MzSb 314 100 41 91 Farmer 10 MzSb 89 59 8.5 288 Farmer 11 MzSb 201 143 61.5 143 Farmer 1 MzCp 162 36 9.5 210 Farmer 2 MzCp 39 97 3 322 Farmer 3 MzCp 100 33 6.5 95 Farmer 4 MzCp 122 134 4 97 Farmer 5 MzCp 96 70 5.5 63 Farmer 6 MzCp 139 28 8.5 114 Farmer 7 MzCp 62 80 14.5 73 Farmer 8 MzCp 129 97 29 212 Farmer 9 MzCp 241 95 53.5 98 Farmer 10 MzCp 37 77 8 76 Farmer 11 MzCp 137 127 31.5 99 Farmer 1 Cp - - - - Farmer 2 Cp 46 38 3.5 194 Farmer 3 Cp - - - - Farmer 4 Cp - - - - Farmer 5 Cp - - - - Farmer 6 Cp - - - - Farmer 7 Cp - - - - Farmer 8 Cp 145 72 45 211 Farmer 9 Cp - - - - 67

Weed density (#) Weed FW (gram/0.25 sq meter) Farmers (Block) Treatment

25 DAS 50 DAS 25 DAS 50 DAS Farmer 10 Cp - - - - Farmer 11 Cp - - - -

xi. Maize and legume yield on different cropping system

Maize grain yield Soybean grain yield Cowpea fresh pod Farmers (Block) Treatment (t/ha) (t/ha) yield (t/ha) Farmer 1 Mz 8.31 - - Farmer 2 Mz 6.80 - - Farmer 3 Mz 10.40 - - Farmer 4 Mz 9.16 - - Farmer 5 Mz 8.21 - - Farmer 6 Mz 5.28 - - Farmer 7 Mz 4.77 - - Farmer 8 Mz 8.95 - - Farmer 9 Mz 6.18 - - Farmer 10 Mz 8.30 - - Farmer 11 Mz 6.45 - - Farmer 1 Sb - 1.93 - Farmer 2 Sb - 1.86 - Farmer 3 Sb - 1.62 - Farmer 4 Sb - 1.92 - Farmer 5 Sb - 1.98 - Farmer 6 Sb - 1.74 - Farmer 7 Sb - 1.95 - Farmer 8 Sb - * - Farmer 9 Sb - 1.62 - Farmer 10 Sb - 1.15 - Farmer 11 Sb - 1.57 - Farmer 1 MzSb 6.47 0.99 - Farmer 2 MzSb 7.10 1.00 - Farmer 3 MzSb 11.26 0.94 - Farmer 4 MzSb 10.45 1.07 - Farmer 5 MzSb 5.71 0.99 - Farmer 6 MzSb 4.35 0.83 - Farmer 7 MzSb 6.68 1.11 - Farmer 8 MzSb 9.56 - - Farmer 9 MzSb 7.39 0.99 - Farmer 10 MzSb 5.46 0.92 - Farmer 11 MzSb 6.21 0.80 - Farmer 1 MzCp 7.74 - 3.39 68

Maize grain yield Soybean grain yield Cowpea fresh pod Farmers (Block) Treatment (t/ha) (t/ha) yield (t/ha) Farmer 2 MzCp 9.41 - 3.14 Farmer 3 MzCp 10.30 - 3.03 Farmer 4 MzCp 7.49 - 2.81 Farmer 5 MzCp 6.88 - 6.10 Farmer 6 MzCp 5.11 - 3.57 Farmer 7 MzCp 5.41 - 4.91 Farmer 8 MzCp 9.69 - 2.06 Farmer 9 MzCp 6.71 - 4.87 Farmer 10 MzCp 9.10 - 3.02 Farmer 11 MzCp 6.64 - 2.43 Farmer 1 Cp - - - Farmer 2 Cp - - 6.48 Farmer 3 Cp - - - Farmer 4 Cp - - - Farmer 5 Cp - - - Farmer 6 Cp - - - Farmer 7 Cp - - - Farmer 8 Cp - - 4.85 Farmer 9 Cp - - - Farmer 10 Cp - - - Farmer 11 Cp - - -

xii. Maize and legume stover DM yield on different cropping system

Maize stover yield Soybean stover yield cowpea stover yield Farmers (Block) Treatment (t/ha) (t/ha) (t/ha) Farmer 1 Mz 9.16 - - Farmer 2 Mz 8.49 - - Farmer 3 Mz 9.84 - - Farmer 4 Mz 10.30 - - Farmer 5 Mz 11.38 - - Farmer 6 Mz 8.11 - - Farmer 7 Mz 7.30 - - Farmer 8 Mz 8.79 - - Farmer 9 Mz 10.05 - - Farmer 10 Mz 13.51 - - Farmer 11 Mz 12.78 - - Farmer 1 Sb - 4.08 - Farmer 2 Sb - 3.64 - Farmer 3 Sb - 3.01 - Farmer 4 Sb - 2.80 - Farmer 5 Sb - 4.43 - Farmer 6 Sb - 4.04 - 69

Maize stover yield Soybean stover yield cowpea stover yield Farmers (Block) Treatment (t/ha) (t/ha) (t/ha) Farmer 7 Sb - 5.91 - Farmer 8 Sb - * - Farmer 9 Sb - 3.14 - Farmer 10 Sb - 4.47 - Farmer 11 Sb - 2.85 - Farmer 1 MzSb 10.42 1.97 - Farmer 2 MzSb 9.87 1.90 - Farmer 3 MzSb 15.25 1.50 - Farmer 4 MzSb 10.77 2.03 - Farmer 5 MzSb 9.16 1.67 - Farmer 6 MzSb 6.77 0.80 - Farmer 7 MzSb 7.10 2.84 - Farmer 8 MzSb 14.29 * - Farmer 9 MzSb 6.13 0.56 - Farmer 10 MzSb 9.02 2.04 - Farmer 11 MzSb 7.59 0.82 - Farmer 1 MzCp 8.50 - 4.56 Farmer 2 MzCp 9.95 - 1.35 Farmer 3 MzCp 11.18 - 0.97 Farmer 4 MzCp 9.56 - 1.12 Farmer 5 MzCp 7.74 - 0.81 Farmer 6 MzCp 6.14 - 1.06 Farmer 7 MzCp 6.21 - 1.54 Farmer 8 MzCp 10.23 - 0.80 Farmer 9 MzCp 6.21 - 2.26 Farmer 10 MzCp 8.22 - 0.44 Farmer 11 MzCp 7.96 - 0.83 Farmer 1 Cp - - Farmer 2 Cp - - 1.43 Farmer 3 Cp - - - Farmer 4 Cp - - - Farmer 5 Cp - - - Farmer 6 Cp - - - Farmer 7 Cp - - - Farmer 8 Cp - - 1.17 Farmer 9 Cp - - - Farmer 10 Cp - - - Farmer 11 Cp - - -

xiii. Partial LER, Total LER , ATER and HI of maize, soybean and cowpea on different cropping system.

Total Partial LER Farmers (Block) Treatment LER Harvest Index Maize Soybean Cowpea Maize Soybean Cowpea ATER Farmer 1 Mz 1 - - 1 0.48 - - 1.00 Farmer 2 Mz 1 - - 1 0.44 - - 1.00 Farmer 3 Mz 1 - - 1 0.51 - - 1.00 Farmer 4 Mz 1 - - 1 0.47 - - 1.00 Farmer 5 Mz 1 - - 1 0.42 - - 1.00 Farmer 6 Mz 1 - - 1 0.39 - - 1.00 Farmer 7 Mz 1 - - 1 0.40 - - 1.00 Farmer 8 Mz 1 - - 1 0.50 - - 1.00 Farmer 9 Mz 1 - - 1 0.38 - - 1.00 Farmer 10 Mz 1 - - 1 0.38 - - 1.00 Farmer 11 Mz 1 - - 1 0.34 - - 1.00 Farmer 1 Sb - 1 - 1 - 0.32 - 1.00 Farmer 2 Sb - 1 - 1 - 0.34 - 1.00 Farmer 3 Sb - 1 - 1 - 0.35 - 1.00 Farmer 4 Sb - 1 - 1 - 0.41 - 1.00 Farmer 5 Sb - 1 - 1 - 0.31 - 1.00 Farmer 6 Sb - 1 - 1 - 0.30 - 1.00 Farmer 7 Sb - 1 - 1 - 0.25 - 1.00 Farmer 8 Sb - 1 - 1 - * - 1.00 Farmer 9 Sb - 1 - 1 - 0.34 - 1.00 Farmer 10 Sb - 1 - 1 - 0.20 - 1.00 Farmer 11 Sb - 1 - 1 - 0.36 - 1.00 Farmer 1 MzSb 0.78 0.51 - 1.29 0.38 0.33 - 1.17 Farmer 2 MzSb 1.04 0.54 - 1.58 0.42 0.34 - 1.42 Farmer 3 MzSb 1.08 0.58 - 1.66 0.42 0.39 - 1.49 Farmer 4 MzSb 1.14 0.56 - 1.70 0.49 0.35 - 1.52 Farmer 5 MzSb 0.70 0.50 - 1.20 0.38 0.37 - 1.09 Farmer 6 MzSb 0.82 0.48 - 1.30 0.39 0.51 - 1.17 Farmer 7 MzSb 1.40 0.57 - 1.97 0.48 0.28 - 1.75 Farmer 8 MzSb 1.07 - - - 0.40 - - - Farmer 9 MzSb 1.20 0.61 - 1.80 0.55 0.64 - 1.62 Farmer 10 MzSb 0.66 0.80 - 1.46 0.38 0.31 - 1.36 Farmer 11 MzSb 0.96 0.51 - 1.47 0.45 0.49 - 1.33 Farmer 1 MzCp 0.93 - - 0.48 - 0.43 - Farmer 2 MzCp 1.38 0.48 1.87 0.49 - 0.70 1.78 Farmer 3 MzCp 0.99 - - 0.48 - 0.76 - Farmer 4 MzCp 0.82 - - 0.44 - 0.72 - Farmer 5 MzCp 0.84 - - 0.47 - 0.88 - Farmer 6 MzCp 0.97 - - 0.45 - 0.77 - Farmer 7 MzCp 1.13 - - 0.47 - 0.76 - Farmer 8 MzCp 1.08 0.43 1.51 0.49 - 0.72 1.43

Total Partial LER Farmers (Block) Treatment LER Harvest Index Maize Soybean Cowpea Maize Soybean Cowpea ATER Farmer 9 MzCp 1.09 - - - 0.52 - 0.68 - Farmer 10 MzCp 1.10 - - - 0.53 - 0.87 - Farmer 11 MzCp 1.03 - - - 0.45 - 0.74 - Farmer 1 Cp ------Farmer 2 Cp - - 1 1 - - 0.82 1.00 Farmer 3 Cp ------Farmer 4 Cp ------Farmer 5 Cp ------Farmer 6 Cp ------Farmer 7 Cp ------Farmer 8 Cp - - 1 1 - - 0.81 1.00 Farmer 9 Cp ------Farmer 10 Cp ------Farmer 11 Cp ------

xiv. Maize grain yield and stover DM yield on farmers practice

Stover yield # grains/cob Grain yield (Mg/ha) Farmers (Block) Treatment (Mg/ha)

Farmer 1 Farmer Practice 371 2.18 3.85 Farmer 2 Farmer Practice 529 3.07 5.48 Farmer 3 Farmer Practice 351 3.25 4.57 Farmer 4 Farmer Practice 381 3.17 4.32 Farmer 5 Farmer Practice 371 2.90 4.60 Farmer 6 Farmer Practice 362 1.46 3.15 Farmer 7 Farmer Practice 309 2.42 4.80 Farmer 8 Farmer Practice 288 2.87 3.85 Farmer 9 Farmer Practice 300 2.92 3.30 Farmer 10 Farmer Practice 285 2.75 4.71 Farmer 11 Farmer Practice 251 2.45 4.03

72 xv. Most repeatedly occuring problematic weeds at on experimental sites